Objective and subjective methods of sales planning. Methods for forecasting sales of goods
This article discusses one of the main forecasting methods - time series analysis. On the example of a retail store, using this method, sales volumes for the forecast period are determined.
One of the main responsibilities of any leader is to correctly plan the work of his company. The world and business are changing very rapidly now, and it is not easy to keep up with all the changes. Many events that cannot be foreseen in advance change the company's plans (for example, the release of a new product or group of goods, the appearance of a strong company on the market, the merger of competitors). But we must understand that often plans are needed only in order to make adjustments to them, and there is nothing to worry about.
Any forecasting process, as a rule, is built in the following sequence:
1. Formulation of the problem.
2. Collecting information and choosing a forecasting method.
3. Application of the method and evaluation of the obtained forecast.
4. Using the forecast to make a decision.
5. Analysis "forecast-fact".
It all starts with the correct formulation of the problem. Depending on it, the forecasting problem can be reduced, for example, to an optimization problem. For short-term production planning, it is not so important what the sales volume will be in the coming days. It is more important to distribute production volumes according to the available capacities as efficiently as possible.
The key constraint when choosing a forecasting method will be the initial information: its type, availability, processing capability, homogeneity, volume.
The choice of a specific forecasting method depends on many factors. Is there enough objective information about the predicted phenomenon (does this product or analogues exist for a long time)? Are qualitative changes expected in the studied phenomenon? Are there relationships between the phenomena studied and/or within the data arrays (sales volumes usually depend on the volume of advertising investments)? Is the data a time series (information about ownership of borrowers is not a time series)? Are there recurring events (seasonal fluctuations)?
No matter what industry or area of business a firm operates in, management must constantly make decisions that will have consequences in the future. Any decision is based on one method or another. One of these methods is forecasting.
Forecasting- this is a scientific definition of the likely ways and results of the upcoming development of the economic system and an assessment of the indicators that characterize this development in a more or less distant future.
Let's consider sales volume forecasting using the time series analysis method.
Forecasting based on time series analysis assumes that changes in sales volumes that have occurred can be used to determine this indicator in subsequent periods of time.
time series - this is a series of observations carried out regularly at regular intervals: a year, a week, a day or even minutes, depending on the nature of the variable under consideration.
Typically, a time series consists of several components:
1) trend - the general long-term trend of change in the time series underlying its dynamics;
2) seasonal variation - short-term regularly repeating fluctuations in the values of the time series around the trend;
3) cyclical fluctuations that characterize the so-called business cycle, or the economic cycle, consisting of economic recovery, recession, depression and recovery. This cycle is repeated regularly.
To combine individual elements of the time series, you can use multiplicative model:
Sales Volume = Trend × Seasonal Variation × Residual Variation. (1)
When compiling a sales forecast, the company's performance over the past few years, the market growth forecast, and the dynamics of competitors' development are taken into account. Optimal sales forecasting and forecast correction provides a complete report on the company's sales.
We apply this method to determine the sales volume of the salon "Clock" for 2009. In Table. 1 shows the sales volumes of the "Chasy" salon, which specializes in the retail sale of watches.
Table 1. Dynamics of the sales volume of the Chasy salon, thousand rubles
For the data given in table. 1, we note two main points:
existing trend: the volume of sales in the respective quarters of each year is steadily growing year by year;
- seasonal variation: in the first three quarters of each year, sales slowly increase, but remain at a relatively low level; the yearly highest sales figures always occur in the fourth quarter. This trend is repeated year after year. This type of variance is always referred to as seasonal, even if it is, for example, a time series of weekly sales volumes. This term simply reflects the regularity and short duration of trend deviations compared to the length of the time series.
The first step in time series analysis is plotting the data.
In order to make a forecast, you must first calculate the trend, and then the seasonal components.
Trend Calculation
A trend is a general long-term trend in the time series underlying its dynamics.
If you look at fig. 2, then through the points of the histogram, you can draw a line of an upward trend by hand. However, for this there are mathematical methods that allow you to assess the trend more objectively and accurately.
If the time series has seasonal variation, the moving average method is usually used. The traditional method for predicting the future value of an indicator is averaging n its past values.
Mathematically, moving averages (serving as an estimate of the future value of demand) are expressed as follows:
Moving average = Sum of demand for the previous n-periods / n. (2)
Average sales for the first four quarters = (937.6 + 657.6 + 1001.8 + 1239.2) / 4 = 959.075 thousand rubles.
When a quarter ends, sales figures for the last quarter are added to the sum of the previous three quarters, and data for the earlier quarter is discarded. This leads to a smoothing of short-term disturbances in the data series.
Average sales for the next four quarters = (657.6 + 1001.8 + 1239.2 + 1112.5) / 4 = 1002.775 thousand rubles.
The first calculated average shows the average sales volume for the first year and is in the middle between the sales data for the 2nd and 3rd quarters of 2007. The average for the next four quarters will be placed between the sales volume for the 3rd and 4th quarters. So column 3 data is the moving average trend.
But to continue the analysis of the time series and the calculation of seasonal variation, it is necessary to know the trend value at exactly the same time as the original data, so it is necessary to center the obtained moving averages by adding adjacent values and dividing them in half. The centered average is the value of the calculated trend (calculations are presented in columns 4 and 5 of Table 2).
Table 2. Time series analysis
|
Sales volume, thousand rubles |
Four-quarter moving average |
The sum of two adjacent values |
Trend, thousand rubles |
Sales volume / trend × 100 |
|
|
I sq. 2007 | |||||
|
II quarter. 2007 | |||||
|
III quarter. 2007 | |||||
|
IV quarter. 2007 | |||||
|
I sq. 2008 | |||||
|
II quarter. 2008 | |||||
|
III quarter. 2008 | |||||
|
IV quarter. 2008 |
To make a sales forecast for each quarter of 2009, you need to continue the trend of moving averages on the chart. Since the smoothing process has eliminated all fluctuations around the trend, this should not be difficult to do. The spread of the trend is shown by the line in fig. 4. According to the schedule, you can determine the forecast for each quarter (Table 3).
Table 3. Trend forecast for 2009
|
2009 |
Sales volume, thous.rub. |
Calculation of seasonal variation
In order to make a realistic sales forecast for each quarter of 2009, it is necessary to look at the quarterly dynamics of sales volume and calculate the seasonal variation. If you look at the sales data for the previous period and ignore the trend, you can see the seasonal variation more clearly. Since for the analysis of the time series will be used multiplicative model, Divide each sales volume by the trend value, as shown in the following formula:
Multiplicative Model = Trend × Seasonal Variation × Residual Variation × Sales Volume / Trend = Seasonal Variation × Residual Variation. (3)
The calculation results are presented in column 6 of Table. 2. In order to express the values of the indicators as a percentage and round them to the first decimal place, multiply them by 100.
Now we will take the data for each quarter in turn and establish how much, on average, they are more or less than the trend values. The calculations are given in table. 4.
Table 4. Calculation of the average quarterly variation, thousand rubles
|
I quarter |
II quarter |
III quarter |
IV quarter |
|
|
unadjusted average | ||||
Uncorrected data in table. 4 contain both seasonal and residual variation. To remove the element of residual variation, the means must be adjusted. In the long run, the amount of sales above trend in good quarters must equalize the amount by which sales are below trend in bad quarters, so that the seasonal components add up to about 400%. In this case, the sum of the unadjusted means is 398.6. Thus, it is necessary to multiply each average value by a correction factor so that the sum of the averages is 400.
Correction factor calculated as follows: Correction factor = 400 / 398.6 = 1.0036.
The calculation of seasonal variation is presented in Table. 5.
Table 5. Calculation of seasonal variation
Based on the data in Table. 5, it can be predicted, for example, that in the first quarter, the sales volume will average 96.3% of the trend value, in the IV - 118.1% of the trend value.
Sales forecast
When compiling a sales forecast, we proceed from the following assumptions:
trend dynamics will remain unchanged compared to previous periods;
seasonal variation will retain its behavior.
Naturally, this assumption may turn out to be incorrect, and adjustments will have to be made, taking into account the expected change in the situation by the expert. For example, another major watch dealer may enter the market and bring down the prices of the “Chasy” salon, the economic situation in the country may change, etc.
Nevertheless, based on the above assumptions, it is possible to make a sales forecast by quarters for 2009. To do this, the obtained values of the quarterly trend must be multiplied by the value of the corresponding seasonal variation for each quarter. The calculation of the data is given in table. 6.
Table 6. Compilation of the sales forecast by quarters of the salon "Clock" for 2009
It can be seen from the obtained forecast that the turnover of the salon "Chasy" in 2009 may amount to 5814 thousand rubles, but for this the enterprise needs to carry out various activities.
Read the full text of the article in the journal "Economist's Handbook" No. 11 (2009).
The realism and feasibility of the company's budget largely depends on how correctly they made a plan for the sale of products and, accordingly, predicted the receipt of revenue. This solution offers several ways to plan sales, from which you can choose the most suitable for the specifics of the company.
Advantages and disadvantages
The decision describes in detail and with examples the procedure for planning sales volumes in physical and monetary terms, as well as coordinating the sales plan with the budget of income and expenses, cash flow. If sales planning is the prerogative of a commercial service, the proposed methodology will be useful to the business owner to verify the validity and correctness of the declared figures.
Since most companies operate in a competitive environment and business success depends on the ability to sell products, consider the option when the sales plan serves as the starting point for budgeting.
How to organize sales planning
Sales are usually planned by businessmen and economists. The first of them predict the state of the market, relationships with customers, determine the value of the coefficients of growth in sales and (or) prices; the latter provide analytical material (based on accounting and (or) management reporting). Depending on what criteria are especially important for the enterprise, the sales plan can be structured in different ways: by counterparties, product range, price groups, conditions, payments, etc. Sales can be planned for the horizon both in a month and several years. As a rule, they are predicted for a year, broken down by months, and for the next few years, without breakdown. If necessary (difficult financial situation and the threat of cash gaps), more detail is possible - for example, only the first (nearest) quarter is disclosed ten days, and then a monthly plan is given.
How to prepare a sales plan
For planning “from what has been achieved”, the basis is information on the dynamics of sales (in physical and value terms) for the previous period, comparable both in duration and seasonality with the planned one. This requirement can be difficult to meet, since sales are usually forecast in the fourth quarter, when the year has not yet ended and the results have not been summed up. In this case, information is used on the actual implementation for the past 9 or 10 months and the planned one for the time remaining until the end of the year (November-December).
If a company applies different VAT rates or engages in several activities that require different taxation systems, then it is especially important for it to forecast sales in terms of value without VAT, so the plan will be more correct. This can also be recommended for companies applying the standard 18% VAT. In the future, when clarifying the directions for using the base forecast (for example, for preparing a cash flow budget, for calculating the tax burden, for setting goals for the sales department, etc.), revenue with VAT should be calculated.
Depending on the range of products, the number of counterparties and other business features, various methods of planning the volume of sales can be used: one product, with details on counterparties and nomenclature, taking into account not only the final cost, but also its components (quantity, price, resource constraints) .
The easiest way to plan sales is to take the sales volume for the base period (the one that is taken as a basis, for example, the last month or the same month of the last year - when planning by months) and adjust it for the desired increase according to formula 1.
Formula 1. Sales plan calculation
This method is used when the company produces only one product, and sales are planned for one month or there are no seasonal fluctuations in demand during the year.
Consider the structure of sales.
Sales volume can be predicted in detail, by goods and/or customers. The calculations are carried out according to formula 1, but the data for the base period is taken in the same analytics (goods or buyers). Moreover, target sales growth rates will also have to be set individually for each type of product (buyer). The forecast is formed for the year as a whole or for periods - but only in the absence of seasonal fluctuations in demand. When planning in the context of customers, the coefficients are set depending on the state of business of counterparties (for example, if the acquiring company is actively developing, you can plan an increase in sales), based on the agreements reached, as well as on the basis of expert assessments of merchants (see Table 1. Sales plan in value terms by counterparties).
Table 1. Sales plan in value terms by counterparties
The item-by-item sales plan is formed taking into account individual sales growth rates for each product, depending on whether it is supposed to increase sales or withdraw the product from the market (see Table 2. Sales plan in value terms by item).
Table 2. Sales plan in value terms by item
You can also provide a two-level structure of the sales plan:
- by counterparties (buyers) and the range of goods purchased by them (see Table 3. Sales plan in value terms by counterparties and products);
- by nomenclature and its buyers (see table 4. Sales plan in value terms by product nomenclature and buyers).
This method allows you to prepare a more detailed plan. Target coefficients are set taking into account both the state of relationships with customers and the company's intentions to promote its products.
Table 3. Sales plan in value terms by counterparties and products
| counterparty | Nomenclature | |||
| Yolochka LLC | Sweets "Breeze" | 1500,00 | 1,015 | 1522,50 |
| Sweets "Grilyazh" | 1000,00 | 1,040 | 1040,00 | |
| Candy "Sweet tooth" | 1500,00 | 1,070 | 1605,00 | |
| Sweets "Sun" | 1000,00 | 1,050 | 1050,00 | |
| Total | 5000,00 | 1,044 | 5217,50 | |
| OOO Zamok | Sweets "Breeze" | 5000,00 | 1,010 | 5050,00 |
| Sweets "Grilyazh" | 2000,00 | 1,040 | 2080,00 | |
| Candy "Sweet tooth" | 2000,00 | 1,075 | 2150,00 | |
| Sweets "Sun" | 1000,00 | 1,015 | 1015,00 | |
| Total | 10 000,00 | 1,030 | 10 295,00 | |
| LLC "Zebra" | Sweets "Breeze" | 1000,00 | 1,110 | 1110,00 |
| Sweets "Grilyazh" | 500,00 | 1,090 | 545,00 | |
| Candy "Sweet tooth" | 1500,00 | 1,100 | 1650,00 | |
| Sweets "Sun" | 1000,00 | 1,040 | 1040,00 | |
| Total | 4000,00 | 1,086 | 4345,00 | |
| LLC "Kangaroo" | Sweets "Breeze" | 7500,00 | 1,010 | 7575,00 |
| Sweets "Grilyazh" | 9500,00 | 1,040 | 9880,00 | |
| Candy "Sweet tooth" | 2000,00 | 1,050 | 2100,00 | |
| Sweets "Sun" | 1000,00 | 1,030 | 1030,00 | |
| Total | 20 000,00 | 1,029 | 20 585,00 | |
| Total | 39 000,00 | 1,037 | 40 442,50 | |
Determination of sales growth factors for counterparties, taking into account the products they purchase, gives somewhat different results than planning only for buyers or only for types of products. Taking into account the two-level structure of sales, it is necessary to analyze not only the trends in relations with the counterparty, but also the state of the market, to correlate the interests of the enterprise in promoting a particular product with the needs and capabilities of customers. This work is more difficult, but its results are more valuable for the company.
Table 4. Sales plan in value terms by product range and customers
| Nomenclature | counterparty | Sales volume for the base period, rub. | Sales growth rate, units | Planned sales volume, rub. |
| Sweets "Breeze" | Yolochka LLC | 1500 | 1,015 | 1522,50 |
| OOO Zamok | 5000 | 1,010 | 5050,00 | |
| LLC "Zebra" | 1000 | 1,110 | 1110,00 | |
| LLC "Kangaroo" | 7500 | 1,010 | 7575,00 | |
| Total | 15 000 | 1,017 | 15 257,50 | |
| Sweets "Grilyazh" | Yolochka LLC | 1000 | 1,040 | 1040,00 |
| OOO Zamok | 2000 | 1,040 | 2080,00 | |
| LLC "Zebra" | 500 | 1,090 | 545,00 | |
| LLC "Kangaroo" | 9500 | 1,040 | 9880,00 | |
| Total | 13 000 | 1,042 | 13 545,00 | |
| Candy "Sweet tooth" | Yolochka LLC | 1500 | 1,070 | 1605,00 |
| OOO Zamok | 2000 | 1,075 | 2150,00 | |
| LLC "Zebra" | 1500 | 1,100 | 1650,00 | |
| LLC "Kangaroo" | 2000 | 1,050 | 2100,00 | |
| Total | 7000,00 | 1,072 | 7505,00 | |
| Sweets "Sun" | Yolochka LLC | 1000,00 | 1,050 | 1050,00 |
| OOO Zamok | 1000,00 | 1,015 | 1015,00 | |
| LLC "Zebra" | 1000,00 | 1,040 | 1040,00 | |
| LLC "Kangaroo" | 1000,00 | 1,030 | 1030,00 | |
| Total | 4000,00 | 1,034 | 4135,00 | |
| Total | 39 000,00 | 1,037 | 40 442,50 | |
Take into account the factors affecting sales growth
The amount of revenue is influenced by two indicators: price and volume of sales in physical terms. When planning, you can take into account the desired dynamics of each of them. Various sources of growth (price and quantity) are taken into account when forming the target percentage of increase (growth) in sales (see formula 2 Calculation of the target percentage of sales growth):
Formula 2. Calculation of the target percentage of sales growth
For example, traders were given the task of increasing sales by 10 percent. However, it is not specified what should be the source of this growth. You can formulate a goal more clearly: increase the quantity of goods sold by 5 percent at a price increase of 6 percent. In this case, the target sales growth would be 11.3 percent ((100% + 5%) × (100% + 6%) : 100% - 100%). Using this method of sales planning, it is necessary to take into account the two-level structure of the forecast for product sales - it can be disclosed both by product type with division by counterparties, and vice versa (see Table 5. Sales plan, taking into account price dynamics and sales volumes). If the company has a large range of products or a wide range of counterparties, it is better to combine the product range or customers into groups. For example, counterparties can be aggregated by region, scope of purchases, purpose of purchasing goods, payment methods, etc.
Table 5. Sales plan taking into account the dynamics of prices and sales volumes
| counterparty | Nomenclature | Fact | Coefficient of price growth, units | Sales volume growth rate, units | Sales growth rate, units | Plan | ||||
| price, rub. | Quantity, kg | Sales volume, rub. | price, rub. | Quantity, kg | Sales volume, rub. | |||||
| Yolochka LLC | Sweets "Breeze" | 50,00 | 30,00 | 1500,00 | 1,05 | 1,06 | 1,113 | 52,50 | 31,80 | 1669,50 |
| Sweets "Grilyazh" | 100,00 | 10,00 | 1000,00 | 1,03 | 1,06 | 1,092 | 103,00 | 10,60 | 1091,80 | |
| Candy "Sweet tooth" | 25,00 | 60,00 | 1500,00 | 1,04 | 1,07 | 1,113 | 26,00 | 64,20 | 1669,20 | |
| Sweets "Sun" | 40,00 | 25,00 | 1000,00 | 1,05 | 1,05 | 1,103 | 42,00 | 26,25 | 1102,50 | |
| Total | – | 125,00 | 5000,00 | – | –- | – | – | 132,85 | 5533,00 | |
| OOO Zamok | Sweets "Breeze" | 40,00 | 125,00 | 5000,00 | 1,07 | 1,09 | 1,166 | 42,80 | 136,25 | 5831,50 |
| Sweets "Grilyazh" | 100,00 | 20,00 | 2000,00 | 1,04 | 1,08 | 1,123 | 104,00 | 21,60 | 2246,40 | |
| Candy "Sweet tooth" | 20,00 | 100,00 | 2000,00 | 1,06 | 1,05 | 1,113 | 21,20 | 105,00 | 2226,00 | |
| Sweets "Sun" | 40,00 | 25,00 | 1000,00 | 1,10 | 1,06 | 1,166 | 44,00 | 26,50 | 1166,00 | |
| Total | – | 270,00 | 10 000,00 | – | – | – | – | 289,35 | 11 469,90 | |
| LLC "Zebra" | Sweets "Breeze" | 50,00 | 20,00 | 1000,00 | 1,08 | 1,10 | 1,188 | 54,00 | 22,00 | 1188,00 |
| Sweets "Grilyazh" | 100,00 | 5,00 | 500,00 | 1,09 | 1,06 | 1,155 | 109,00 | 5,30 | 577,70 | |
| Candy "Sweet tooth" | 25,00 | 60,00 | 1500,00 | 1,11 | 1,10 | 1,221 | 27,75 | 66,00 | 1831,50 | |
| Sweets "Sun" | 40,00 | 25,00 | 1000,00 | 1,06 | 1,09 | 1,155 | 42,40 | 27,25 | 1155,40 | |
| Total | – | 110,00 | 4000,00 | – | – | – | – | 120,55 | 4752,60 | |
| LLC "Kangaroo" | Sweets "Breeze" | 34,90 | 215,00 | 7500,00 | 1,20 | 1,10 | 1,320 | 41,88 | 236,39 | 9900,00 |
| Sweets "Grilyazh" | 95,00 | 100,00 | 9500,00 | 1,09 | 1,03 | 1,123 | 103,55 | 103,00 | 10 665,65 | |
| Candy "Sweet tooth" | 20,00 | 100,00 | 2000,00 | 1,08 | 1,04 | 1,123 | 21,60 | 104,00 | 2246,40 | |
| Sweets "Sun" | 40,000 | 25,00 | 1000,00 | 1,06 | 1,06 | 1,124 | 42,40 | 26,50 | 1123,60 | |
| Total | – | 440,00 | 20 000,00 | – | – | – | – | 469,89 | 23 935,65 | |
| Total | – | 944,90 | 39 000,00 | – | – | – | – | 1012,64 | 45 691,15 | |
Situation: how to make a revenue forecast based on the sales budget
To prepare a cash flow budget, it is necessary to plan sales by months, preferably in the context of counterparties, as this will allow you to take into account the dynamics of receivables. Revenue is projected with VAT. If the company does not apply the special rates of this tax (10% and 0%), then the entire planned sales volume is multiplied by 18 percent (see table 8. Sales plan in terms of value with VAT for the cash flow budget). Otherwise, you will need to group counterparties and sales by them, and then multiply the received sales volumes by the corresponding tax rates. When making a cash flow budget, do not forget to adjust the sales plan for growth and receivables repayment. If the terms of payment for all counterparties are the same (for example, payment within 14 calendar days after shipment), you can refine the general sales plan for the rollover receivable. Under different payment conditions, it is necessary to group buyers by the duration of the delay (see Table 9. Adjustment of the sales plan in value terms with VAT for the cash flow budget).
Table 6. Sales plan in value terms with VAT for the cash flow budget (fragment)
| counterparty | January | … | December | Total for the year | ||||||
| Sales growth rate, units | Planned sales volume, rub. | … | Sales volume for the same period last year, rub. | Sales growth rate, units | Planned sales volume, rub. | Sales volume for the same period last year, rub. | Sales growth rate, units | Planned sales volume, rub. | ||
| Yolochka LLC | 500,00 | 1,05 | 525,00 | … | 400,00 | 1,05 | 420,00 | 6000,00 | 1,05 | 6300,00 |
| OOO Zamok | 600,00 | 1,04 | 624,00 | … | 700,00 | 1,04 | 728,00 | 7800,00 | 1,04 | 8112,00 |
| LLC "Zebra" | 300,00 | 1,10 | 330,00 | … | 150,00 | 1,10 | 165,00 | 3000,00 | 1,10 | 3300,00 |
| LLC "Kangaroo" | 2000,00 | 1,03 | 2060,00 | … | 1500,00 | 1,03 | 1545,00 | 21 000,00 | 1,03 | 21 630,00 |
| Total | 3400,00 | – | 3539,00 | … | 2750,00 | – | 2858,00 | 37 800,00 | – | 39 342,00 |
| VAT (18%) | 612,00 | – | 637,02 | … | 495,00 | – | 514,44 | 6804,00 | – | 7081,56 |
| Total with VAT | 4012,00 | – | 4176,02 | … | 3245,00 | – | 3372,44 | 44 604,00 | – | 46 423,56 |
Table 7. Adjustment of the sales plan in value terms with VAT for the cash flow budget (fragment)
| Index | January | February | March | April | May | … |
| Accounts receivable at the beginning of the period, rub. | 30 000 | 31 250 | 27 500 | 32 750 | 36 250 | … |
| Sales volume, rub. with VAT, including: | 75 000 | 65 000 | 74 000 | 85 000 | 73 000 | … |
| 14 calendar days deferred payment (approximately 50% of sales are paid in the next month) | 50 000 | 45 000 | 57 000 | 60 000 | 55 000 | … |
| Yolochka LLC | 20 000 | 25 000 | 27 000 | 30 000 | 25 000 | … |
| OOO Zamok | 30 000 | 20 000 | 30 000 | 30 000 | 30 000 | … |
| deferred payment of 7 calendar days (approximately 25% of sales are paid in the next month) | 25 000 | 20 000 | 17 000 | 25 000 | 18 000 | … |
| LLC "Zebra" | 10 000 | 10 000 | 10 000 | 10 000 | 10 000 | … |
| LLC "Kangaroo" | 15 000 | 10 000 | 7000 | 15 000 | 8000 | … |
| Scheduled accounts receivable, rub., including length: | 31 250 | 27 500 | 32 750 | 36 250 | 32 000 | … |
| 14 days | 25 000 | 22 500 | 28 500 | 30 000 | 27 500 | … |
| 7 days | 10 000 | 5000 | 4250 | 6250 | 4500 | … |
| Income taking into account the increase (repayment) of receivables (receivables at the beginning of the period + sales volume - planned receivables) | 73 750 | 68 750 | 68 750 | 81 500 | 77 250 | … |
Situation: how to account for marketing promotions and periods of shortage in the sales forecast
Sales should be planned based on demand, and not on the dynamics of sales volumes for past periods. After all, demand can be artificially limited by the size of supplies or a shortage in the warehouse. When underestimations are used for forecasts, this leads to another deficit. The situation with marketing promotions is reversed. For some time, the demand is artificially increased by the ongoing action. If, when planning purchases, to focus on data for this period, then expectations will be unreasonably high.
There are several approaches to processing information for periods of marketing promotions and shortages. One way is to completely exclude periods with unreliable indicators and not take them into account when planning. However, using this approach, you may encounter the fact that significant information about the change in the sales trend or seasonality will be missed. Moreover, the volume of historical data will be significantly reduced. Therefore, it is better to use an alternative method and carry out a recovery in demand - to clear it of uncharacteristic peaks and recessions. The easiest way is to replace these values with averages for reliable periods. A more complex option is to generate data for past periods of marketing promotions and shortages using hindsight forecasting.
The resulting reconstructed figures serve as a more accurate assessment of the real demand for products. In addition, on the basis of this information, it is possible to calculate the lost profit from the shortage and the additional profit from the marketing campaign. Sometimes it should be considered as unreliable and a period of decline in demand after a marketing campaign. During it, buyers purchase goods for a longer period than usual. Often, a significant rise is followed by a decline in sales. Restoring demand for this period, we can calculate the negative effect of the marketing campaign. Comparison of data (actual for the period of sales decline after the marketing campaign and taking into account the restored demand for the same time) will allow us to evaluate the profitability of the campaign and decide on the advisability of repeating it. After a shortage, on the contrary, there may be an increase in sales. However, it is worth considering what products the company sells. If they can be easily purchased by buyers from other suppliers, then there will be no sharp surge in demand and the data for this period can be considered reliable.
Most of the organizations that exist today were created for the sake of making a profit (organizations created "for the soul" are not taken into account). And each employee of the company in one way or another affects the size of this very profit. In order to get the result, it is necessary to set the "bar" of what each specialist should strive for.
Thus, The first reason why we need a forecast is goal setting.
Some companies aim to increase revenues, others - to increase the number of transactions, and still others - to intercept customers from competitors. We will not describe in detail the methods of setting goals within the framework of this article. We offer just a few methods.
1.SMART. The goal should be Specific (concrete), Measurable (measurable), Attractive (attractive), Realistic (realistic), Time framed (defined in time).
2. Principle of VODKA (a kind of SMART in Russian). The goal should be Inspiring, Timed, Audacious but achievable, Specific, Measurable.
3. CHIRKOR criteria . The goal must be Clear, Measurable, Realistic, Specific, Defined in time and space, formulated in terms of the Result, in the Language of the executor.
Secondly, why do we need a forecast, - to calculate the required human resource to achieve the goal.
Any sales department is first of all people. People who earn "bread and butter" for themselves, and for related departments, and for the owners of the company. And how many people are needed to fulfill the sales plan? We sit down and count, based on the number of clients, the period of contact with each of the clients, the time for reactive activity, etc. The main thing - remember that without a staffed sales department, the chances of realizing the plans are reduced.
Example 1
Calculation of the number of sales department.
Suppose a company cooperates with 500 clients, which are divided into groups (A, B, C). For each group, a standard for the frequency of contacts with clients is set:
Group A - 1 visit in 2 weeks + 1 call in 2 weeks. It takes 30 minutes for a visit + 30 minutes for the road + 10 minutes for a telephone conversation.
Group B - 1 visit per month + 1 call per month. It takes 20 minutes for a visit + 20 minutes for moving + 10 minutes for a telephone conversation.
Group C - 1 call per month, 10 minutes per conversation.
Let's say the base is divided as follows.
Group A clients - 50 people.
Group B clients - 150 people.
Group C clients - 300 people.
Thus, for group A clients we spend: 50 clients x (2 visits per month x 60 min + 2 calls per month x 10 min) = 7000 min (117 working hours).
For group B clients we spend: 150 clients x (1 visit per month x 40 min + 1 call per month x 10 min) = 7500 min (125 working hours).
For group C clients we spend: 300 clients x 1 call per month x 10 min = 3000 min (50 working hours).
Thus, it takes a month to communicate with clients: 117 hours (group A) + 125 hours (group B) + 50 hours (group C) \u003d 292 hours.
Suppose, after subtracting the time for entering into the database, extracting documents, planning meetings, etc. the specialist has 5 working hours per day for direct work with clients (5 hours per day x 21 working days = 105 active hours per month).
It turns out that this company needs:
292/105 = 2.8 (~ 3 specialists to work with 500 clients).
Third, why you need a sales forecast, - inventory management . Without a sales forecast, we will either be in a situation of shortage of goods, or in a situation of excess stock. And in the first, and in the second case, we lose money.
Example 2
The company is engaged in the sale of fans. Demand in one of the seasons due to the established heat was as high as ever. Customers called every day, and the warehouses were already empty. As a result - lost profits and dissatisfied customers.
Example 3
The company flooded the warehouse with snow shovels (in anticipation of Javier's repeat). The winter turned out to be little snowy, and the goods remained in stock until the next winter. As a result - loss of profit, losses due to the cost of renting a warehouse, etc.
Of course, someone may object, saying that in both the first and second cases, weather conditions were to blame. Agree. But at the same time, I note that if a company sells a product that depends on the temperature outside, then the weather forecast should be included in the calculation of the sales forecast.
Fourth factor- it's mobility . In the case of working in several markets, the sales forecast allows you to redeploy efforts to the required market in advance, thereby reducing the risks and costs of a seasonal decline or rise in sales.
Example 4
The company is engaged in the sale of agricultural plant protection products, i.e. The product is highly seasonal. During the season, the company concentrates on the main product; during the off season, it sells inventory that is needed all year round.
An important advantage of having a sales forecast is also the possibility of prompt intervention in the process. This means that in the event of a subsidence of indicators for a particular specialist or for a particular SKU, the management of the department / company can take measures as quickly as possible to correct the actions of a specialist or in relation to the SKU.
Example 5
According to the forecast, the specialist must sell 1000 units of goods per month, but in fact he sold 100. Only a prompt analysis of the causes and the adoption of measures can “save” the following months. And in the absence of a forecast, management could catch this dynamics only at the end of the reporting period (for example, a year), and even then it is unlikely if there is no sales plan.
Now let's move on to the answer to the question: "Who needs a sales forecast?"
Let's divide it into two parts.
- Which companies need a sales forecast?
- Who needs a sales forecast in a company?
1. To all companies involved in active sales, of course, a sales forecast is needed (for what - see above). At the same time, there are companies that are engaged only in shipment on demand (passive sales). For them, the sales forecast does not make much sense, because. sales are more dependent on marketers and advertising specialists in the company. Although some of the forecasting elements here also have a place to be.
2. The forecast is needed by the company's management in order to plan the company's activities and profits. As a result, it is possible to plan expenses for staff training, updating the material base of the office, bonuses, etc.
The forecast is needed by sales specialists and the head of the sales department, because directly responsible for its implementation.
Marketing needs a forecast in order to plan its activities to maintain existing and bring new products to the market.
The forecast is needed for production and logistics to carry out and coordinate their activities.
And now it is logical to talk about who exactly should be involved in sales forecasting in the company. Despite the fact that this process is complex, affecting all departments of the company, the following categories of employees should be involved in forecasting.
- Company top management
- Marketing divisions. Can provide information about trends and market trends
- Heads of sales departments. These are people who are most often between two fires: from above - the "wishlist" of the leadership, from below - the whining of specialists about the impossibility of fulfilling plans. Sales leaders see the situation from the inside and take responsibility for the implementation of the plan
- Sales specialists. Who else but they know the needs of customers better than others
- Logistics and production divisions - in terms of production capacities and logistics capabilities (warehouse, transport, etc.)
At the same time, it is important to remember that if several divisions in a company are engaged in forecasting, then the forecasting methodology should be unified.
If we briefly describe the forecasting procedure itself, then we can conditionally distinguish the following elements (we will do this using the example of a children's goods store).
Macroeconomic forecast. Will include a demographic estimate, birth rate, estimated inflation rate, unemployment, customer spending and savings, government spending on family support, and other factors relevant to the operation of a baby store.
Industry development forecast . How many stores are in this area? Are you planning to enter foreign chains? What consumer are the competitors targeting?
Company sales forecast. Actually, the volume of projected sales, based on the external and internal factors described above.
Having on hand analytics on the macroeconomic situation, the forecast for the development of the industry, the capabilities of our company, we can, using one method or another, make a sales forecast for the future period.
But planning and forecasting does not end after writing the final document - the "sales forecast". It continues in the process of execution of plans. This clearly demonstrates Deming-Shewhart principle, or PDCA algorithm(Plan Do Check Act - planning action check adjustment).
(See fig. 1.)
As you can see from the figure, this is an iterative cycle in which, moving through the steps, we take the following actions: if at the Check step it turns out that everything is fine and the goal has been achieved, then the Act step (React) will be to go to the Plan step and set new goals and objectives. If on the Check step it is found that circumstances have changed (the result is not achieved), then the Act step (Correct) will be to make adjustments and go to the Plan step (Plan), in which we clarify the previously set goal and plan to achieve it.
In conclusion, it should be noted that the forecast itself is not a guarantee that the plan will be fulfilled. To achieve the goals, you need to make the efforts of all employees of your company.
Making a profit is the main goal of any commercial enterprise, which can only be achieved through the sale of a product or service. Therefore, sales is a key function of the company, and the planned sales volume is a tool for planning, controlling and adjusting the activities of the sales department.
Sales planning begins with sales forecasting. Before we start discussing this topic, let's list the key concepts:
- market potential;
- sales potential;
- sales forecast;
- sales quota.
The potential of the market is its full volume, i.e. the maximum number of units of a good or service that can be sold in the entire market by all its participants under ideal conditions. Suppose that 300,000 families live in the city of Ensk. Since the average family rarely purchases more than one refrigerator, it can be said that Enske's refrigerator market potential is 300,000.
Sales potential (sales potential) - the number of units of a product or service that a given company can sell. If the company is a monopolist (which is rare), then the sales potential is theoretically equal to the market potential. However, in real life, most organizations operate in a highly competitive environment and can only rely on a share of the aggregate market. Let's assume that there are 30 suppliers in the refrigerator market in Ensk and they all sell one refrigerator model (we will not take into account the marketing efforts of these companies, their strengths and weaknesses, their product range at the moment). Then all consumers will be divided equally among all 30 companies, respectively, the sales potential of each of the 30 companies will be equal to 10,000 refrigerators (300,000 families / 30 suppliers = 10,000 families that can buy refrigerators).
A sales forecast is the number of units of a product or service that a particular company can sell, given market constraints. In practice, the scenario approach to sales calculation is more often used, which gives two forecasts - pessimistic and optimistic. Assume that a market constraint for a particular refrigerator supplier in Ensk prevents it from delivering goods more than ten kilometers from its warehouse, and the firm is the only supplier in that area with 5,000 potential customers. When making a sales forecast, the optimistic forecast will be 5,000 refrigerators, and the pessimistic forecast (subject to a number of other restrictions) will be 2,000. (Sales forecasting methods will be discussed later in this chapter.) The resulting sales forecast is compared with the market potential and sales potential. If the company is not a monopolist, then the sales forecast will always be less than the sales potential and market potential. If, for any reason, the sales forecast turns out to be greater than the sales potential and the market potential, then the calculations are incorrect, and using such a sales forecast to develop a company's marketing strategy may result in losses.
Sales quotas are the number of units of a product or service that must be sold by a particular sales person. Sales quotas are a key metric for evaluating salespeople's performance in selling a particular product over a given period of time. Assume that the vendor described above has four salespeople serving the same number of customers who will buy the same number of refrigerators. Based on a sales forecast of 2,000 units, each of the four sellers will have a sales quota of 500 refrigerators (2,000 from the sales forecast / 4 salespeople = 500 units). The relationship of the considered concepts is shown in fig. 1.
Rice. 1. Market potential, sales potential and sales forecasting
As can be seen from fig. 1, you first need to assess the factors of the economic environment, namely: competition in the market and the economic, legislative, political and other conditions in which companies operate. After analyzing the economic environment and collecting all the necessary information (number of consumers, their purchasing preferences, etc.), the company can assess the potential of the market. Knowing the potential of the market, its strengths and weaknesses, and the advantages of its product, the company can assess its sales potential. After that, you need to take into account all other market constraints, make an initial sales forecast and compare it with the company's goals. If the initial sales forecast matches these targets, then the forecast can be approved. However, in practice, the sales forecast is accepted after numerous revisions.
Adjusting the sales forecast often leads to a revision of the company's goals. The main task of the process is to ensure that the sales forecast matches the company's goals. Based on the accepted sales forecast, a budget is drawn up for planning all the activities of the company and its divisions, and quotas are distributed to all sales employees.
Sales forecasting methods
Sales forecasting is one of the most important information tools for planning the activities of both the company as a whole and each of its divisions. For example, the finance department uses the sales forecast to plan cash flows, make investment decisions, and draw up operating budgets; production department - for determining volumes, scheduling production and managing inventories; personnel department - for planning the need for employees and as initial information when concluding collective agreements; Purchasing department - for planning the company's total need for materials and scheduling their supply; marketing department - to plan marketing and sales programs and allocate resources between various types of marketing activities. At first glance, it might seem that the larger the company, the more important the accuracy of the forecast; in fact, there is no fundamental difference between a mistake made in forecasting the sales of a kiosk and a mistake made in forecasting the sales of a large plant. Errors in forecasting sales of start-up firms are especially dangerous - because, unlike more experienced companies, as a rule, they do not have additional resources to cover the deficit that may arise as a result of improper planning.
The sales forecast is also used to plan and evaluate the performance of each salesperson. It is used to set sales quotas, generate pay plans, and evaluate sales force performance, so it is essential for sales managers to be familiar with basic sales forecasting techniques. For forecasting sales, subjective and objective methods are used (Fig. 2).
Rice. 2. Classification of sales forecasting methods
Subjective methods of sales forecasting
Subjective sales forecasting methods do not use quantitative (empirical) and analytical sales data when making a forecast, but are based on the subjective opinions of various specialists.
User expectations
The user expectation method in sales forecasting is also known as the buyer intention method, because it is based on the statements of consumers about their readiness to purchase a particular product.
The user expectations method in sales forecasting usually produces estimates that are closer to market potential or sales potential than to sales forecasts. This method can be used more as an indicator of the attractiveness of a particular market or its segments for a company than as a sales forecasting tool. In most cases, buyer intentions are separated from the actual purchase by a huge chasm that the company's marketing plan must overcome. It is especially important to keep this gap in mind when developing and introducing new products or services to the market.
The disadvantages of this method are obvious. Often a company spends a lot of money on marketing research, and then fails to sell a new product, the need for which seemed obvious in the research materials. This suggests that the sales forecast based on the user expectations method may give incorrect results. To plan its activities, a company needs to know what exactly the consumer wants to receive from a product or service. Suppose a customer wants to spend less time shopping for groceries. Only a firm (not a consumer), having all the information about the market and demand, can set the task: to build a store in a new densely populated area or organize the sale of products via the Internet with home delivery.
Sometimes using the user expectations method to plan the activities of a company can lead not only to a gross mistake, but also to a complete failure of the project. A similar lesson was learned by Kawasaki when it launched its jet ski. The company, which was the leader in the motorboat market, carefully researched consumer preferences and came to the seemingly indisputable conclusion that in order to defeat competitors in the jet ski segment, it was necessary to produce a model in which the user would receive maximum legroom (at that time all jet skis issued without seats). Kawasaki focused on what consumers wanted and developed a model that truly delivers maximum comfort and is best in class. But while Kawasaki was developing and bringing this model to market, its competitors came up with a model of a jet ski that you could sit in. Of course, Kawasaki failed.
Therefore, the expectation method is best used in combination with others that give more accurate forecasts, and remember the subjectivity of consumers and their limited vision of problems. After all, consumers are not experts in product development, they can only evaluate existing products and offer only their vision of the end result, but in no case recommendations on how to solve problems (more space in the car, laundry near the house, etc.). Henry Ford put it this way: “If I could do what my customers want, I would make fast horses instead of cars.”
Sellers opinion
The sales forecasting method based on the opinion of salespeople or sales personnel is the identification of data on how much product each sales employee expects to sell during a certain period.
The resulting estimates are checked, discussed and adjusted at different levels of management, taking into account the accuracy of the previous forecasts of each sales representative. For various reasons, employees can either underestimate or overestimate their capabilities. For example, if a company's products are in short supply (for example, due to a shortage of raw materials or a rapidly growing market) or available only to a limited number of customers (for example, in the case of a short-term sales promotion campaign), sales personnel overestimate their ability to expectation that more "scarce" goods will be allocated to them. If sales quotas are derived from forecasts, then sales personnel tend to underestimate possible sales volumes in order to get a smaller quota and fulfill it without undue effort. Having exceeded the predicted indicators, such an employee will establish himself as an effective seller and may even receive material rewards.
The opinion of company managers
A sales forecasting method based on the identification of estimates or collective opinions of company managers / leaders of the company is a formal or informal survey of key executives conducted within the selling firm to obtain their estimate of future sales. All expert estimates are combined into a company's sales forecast—sometimes by simply averaging individual estimates. In other cases, apparently divergent points of view of the respondents are discussed in a group, where a consensus is reached. The initial positions of experts may mean nothing more than an intuitive guess of one or another leader about the future development of events. It happens that the leader's opinion is based on rich factual material, and sometimes even on the initial forecast, made in some other way.
Delphi method
The Delphi method allows you to get a more accurate forecast. It is based on an iterative, repeated measures approach with controlled anonymous feedback (instead of face-to-face communication between experts and their discussion of their estimates of future sales). At the same time, each expert prepares his own forecast based on the facts, data and general knowledge of the environment in which the company operates. Then the coordinator draws up a summary report based on the received forecasts and hands it over to each of the participants. As a rule, this report contains the individual forecasts of each expert, the calculated average and the spread of estimates. Typically, experts whose initial estimates diverge sharply from the average are asked to justify their point of view, and these opinions are also included in the final document. Participants of the "survey" study it and offer a new version of the forecast. Usually experts come to a consensus as a result of several iterations. Experience shows that the scatter of data gradually decreases as the estimates of experts converge, and the collective opinion of the group gives a result close to the objective indicators.
Objective Sales Forecasting Methods
Objective sales forecasting methods are based mainly on quantitative (empirical) and analytical data.
Market testing
The market testing method involves selling a product in several geographic regions that are considered representative to determine the reaction of consumers, and then projecting the data obtained to the entire market as a whole. Often this method is used to develop a new product or improve an old one.
Many firms view market testing results as the most important indication of consumer attitudes towards a new product and the ultimate indicator of market potential. Research shows that about three out of four products that receive consumer approval in market testing succeed in the marketplace, and four out of five products that fail testing fail. Still, market testing has a number of disadvantages.
- Its implementation is associated with high costs; it is more suitable for testing consumer products than industrial products.
- Conducting a market test can take a long time.
- When a product is tested on the market, it receives much more attention than it would later receive in a "natural" sale, which creates a distorted view of its potential.
- A market test "opens the cards" for competitors, they have time to formulate their own offer even before the tested products appear on the market in full.
Nevertheless, despite its disadvantages, market testing is a very effective method of forecasting sales. However, it should be applied only after the company's management carefully weighs all its advantages and disadvantages.
Time series analysis
Sales forecasting using time series analysis is based on the analysis of historical data. In the simplest case, the forecast assumes that sales in the next year will be equal to sales in the current year. Such a forecast may be quite accurate for a mature industry characterized by low market growth rates. In other circumstances, it is necessary to use more sophisticated methods of time analysis. s x rows. Here we will look at the following methods:
- moving average;
- exponential smoothing;
- decomposition.
moving average method
The moving average method is quite simple. Let's consider the forecast, which boils down to the fact that sales in the next year will be equal to sales in the current year. With significant fluctuations in sales from year to year, such a forecast is fraught with serious consequences. To take into account all the nuances, you can calculate the average value of several indicators of sales volumes for certain periods of time, for example, to average sales volumes for the last two, three, five years, or for another number of periods convenient for calculations. With this approach, the sales forecast turns out to be the usual average value of sales volumes. The number of indicators used in the calculation is determined experimentally. Ultimately, the number of periods that will provide the most accurate forecasts of verifiable data will be used to develop the forecast model. The term "moving average" is used because the computed new average serves as a prediction at each observation point as new data becomes available.
Exponential smoothing method
When predicting the next value, the moving average method gives equal weight to each of the last n values, where n is the number of years used. Thus, when n = 4 (that is, a four-year moving average is used), the sales forecast for the next year is assigned the same weight to sales for each year of the last four years.
The exponential smoothing method is a variation of the moving average method. Its difference is that the largest weight coefficients are assigned not to all observations, but to the most recent ones, since they carry more information about the likely development of events in the near future.
The effectiveness of the exponential smoothing method largely depends on the choice of the so-called smoothing constant, which is denoted as a in the calculation algorithm and ranges from 0 to 1. High values of a give more weight to the latest observations and less weight to the earlier ones. If sales volumes change insignificantly over time, then it is advisable to use low values of a. However, when sales volumes fluctuate widely, high values of a should be used, causing the forecast series to reflect these changes. Usually the value of a is determined empirically, i.e. different values of a are checked and, as a result, the one that provides the smallest forecast error for a certain number of observations for previous time periods is accepted.
Decomposition Method
If it is necessary to analyze data for shorter periods of time, such as a month or a quarter, in the presence of seasonal fluctuations in sales, when management wants to receive sales forecasts not only for the year, but also for its individual periods, a sales forecasting method called decomposition is used. Here it is important to determine what share of the change in sales volumes is due to market trends, and what is explained by the seasonality of demand. The essence of the decomposition method is to identify four components of the time series:
- trend;
- cyclic factor;
- seasonal factor;
- random factor.
The trend reflects the long-term changes that are observed in the time series when the cyclical, seasonal and irregular components are excluded. It is usually assumed that the trend can be represented as a straight line.
The cyclical factor is not always present, as it reflects the ups and downs (“waves”) in the time series, when the seasonal and random components are excluded. Cyclical booms and busts tend to occur over a fairly long period of time—about two to five years. Some commodities (such as canned corn) experience slight cyclical fluctuations, while sales of others (such as housing construction) experience very large changes.
Seasonality reflects annual fluctuations in the time series caused by the natural change of seasons. The seasonal factor tends to show up annually, although the exact pattern of sales may change from year to year.
The random factor reflects the impact that can be observed after the influence of the trend, cyclical and seasonal factors has been excluded.
Statistical demand analysis
The relationship between sales volumes and certain periods of time, which is used in the time series method, forms the basis for making a forecast for the future. Statistical analysis of demand is an attempt to determine the relationship between sales volumes and the main factors of influence and, on this basis, make a forecast for the future. As a rule, regression analysis is used to evaluate such a relationship. At the same time, the emphasis is on highlighting not all factors that affect sales volumes, but only the most significant ones that have the greatest impact on sales volumes. For example, a plastic window company might take into account factors such as residential construction cycles, interest rate fluctuations, and seasonal increases in demand during spring and summer when forecasting sales.
All sales forecasting methods have their advantages and disadvantages, so the decision to use one method or another is far from obvious. First of all, the decision to use the forecasting method depends on the product or service itself. For example, none of the methods can be used to predict sales of a completely new and unlike product (for example, Tamagotchi toys), since possible sales can range from zero to billions of rubles. We will discuss how to choose the right sales forecasting method later in this chapter.
Choosing a Sales Forecasting Method
Which forecasting method to choose to get the most reliable results? This issue becomes especially relevant when the predictions obtained using different methods do not match. It should be noted that this situation is the rule rather than the exception.
In general, a comparison of different sales forecasting methods shows that none of them can be called the best. The choice of one or another method is influenced by a number of factors. To achieve the optimal result, apparently, one should use several different forecasting methods (objective and subjective), analyze the results obtained and make a final decision on which of the obtained forecasts should be preferred.
When compiling sales forecasts, many firms turn to such a method as scenario analysis. When using this method, forecasters must consistently answer a series of “what if…” questions. It considers both unlikely changes and more likely events. The main idea of this approach is not so much to develop one "correct" scenario, but rather to obtain a set of scenarios that take into account the most important factors that drive the entire system, their interrelations and critical uncertainties.
Demand forecast by territories
Companies need to develop not only methods for assessing demand in general, but also forecasts for individual territories, due to the fact that the sales potential of a particular product cannot be the same for all regions. Territorial demand assessment ensures high efficiency of planning and control over the activities of sales personnel. It is also necessary to perform a number of other important functions of the company, the main of which are:
- marketing territory planning;
- development of methods for identifying potential customers;
- setting sales quotas;
- development of the scheme of remuneration of the sales staff of the company;
- evaluation of the effectiveness of sales personnel.
Territorial demand is assessed differently in industrial and consumer markets. Territorial demand in the industrial market depends on the number of enterprises in the region and their needs for the company's products.
At the same time, sellers of consumer goods most often proceed from the generalized conditions inherent in each of the territories. These conditions are determined by factors such as the number of families, population, or income level in the respective region. It happens that a company tries to correlate demand with several interrelated variables. For example, a statistical analysis of the demand for refrigerators performed using regression analysis shows that this demand is a function of the following variables:
- the number of refrigerators available to consumers;
- the number of residential buildings to which electricity is supplied;
- the amount of real income per family;
- the possibility of obtaining a loan.
With the data in hand, a company can use the appropriate regression to estimate the level of demand across different geographies.
Quotas
As noted at the beginning of the chapter, each employee in the sales department is assigned specific sales targets, or quotas. They are set for a certain calendar period convenient for the organization (month, quarter, year) and can take monetary and physical terms. Quotas are a valuable tool that allows you to plan sales volumes and cash receipts in a specific period of time, as well as evaluate the performance of sales staff and adjust their activities.
Characteristics of the correct quota
The correct quota should be:
- achievable;
- understandable;
- complete;
- timely.
As a rule, quotas for sales volumes for a given territory are set below the sales potential, but equal to the sales forecast (or slightly exceeding it). Sometimes (under unfavorable market conditions, etc.) quotas may be set below the sales forecast. There is an opinion that quotas should be set at a high enough level so that sales personnel make every effort to achieve them. At the same time, inflated quotas allegedly stimulate employees to the maximum return more than real ones. However, behind the external attractiveness of such a scheme, serious shortcomings are hidden: malevolence and hostility between employees, caused by the desire to fulfill their quota at all costs, and a change in attitude towards customers, in particular, the imposition of services that they do not need. Therefore, the practice of using inflated quotas is the exception rather than the rule, and is not effective in the long run. Establishing inflated quotas can only be justified when it is necessary to quickly achieve set short-term goals, for example, when entering a new market. In general, when setting quotas, the approach prevails when realistically achievable tasks are set before sales representatives, supported by good motivation.
Sales quotas should not only be achievable, they should be understandable. If, in the new calendar period, employees are given inflated quotas without taking into account their experience, qualifications, the results of fulfilling the quota in the previous period, the demand for these products, the general market situation and other factors, this approach may cause distrust among the staff and not motivate, but rather, dampen. When setting new quotas, it is necessary to explain to sales representatives how they are formed, because employees are more likely to agree with new tasks if they are familiarized with the reasoning and link indicators with market potential.
The next characteristic of a proper quota is completeness. It combines all the criteria by which the performance of sales staff will be evaluated. For example, if sales personnel are tasked with finding and establishing relationships with new customers, it is necessary to indicate the approximate number of new customers or the percentage of existing ones. If this is not done, the search for new customers will recede into the background or even further, and the primary task for the average worker will be to increase sales and generate profits. Accordingly, it is necessary to adjust the quotas for fulfilling the sales volume so that there is time in the employee’s work schedule to search for and attract new customers.
Finally, the quota distribution system should include timely informing sales representatives about the quota calculation system, their changes and the results of evaluating the performance of each employee. Sales quotas for a given calendar period must be timely calculated and communicated to employees. Delays not only negate the benefits of using quotas, but also create an atmosphere of uncertainty, as employees do not know how their work is valued.
The Role of Quotas in Sales Personnel Management
So, the quota scheme serves as one of the tools that facilitate the planning and control of the activities of the sales force in the field. It has two main advantages:
- the sales quota creates incentives for sales staff;
- helps evaluate the performance of sales staff.
Setting quotas serves as an incentive for sales personnel because it represents a specific goal to be achieved. For example, an employee is given a very specific task - to sell a certain number of units of production in a given reporting period or to conclude transactions for a specific amount. Particularly powerful incentives are the receipt of material rewards or the achievement of a certain social status (the title of "best seller" and the corresponding privileges) when the quota is met or exceeded. In many organizations, the fulfillment of staff quotas is directly linked to the payroll scheme, such as the payment of commissions or bonuses. The following forms are widely used:
- commission plan - wages depending on the total number of goods sold;
- bonus payment plan - the payment of a certain allowance for sales in excess of the established indicator.
Quotas can be considered as an incentive even with a fixed wage (rate) if the fulfillment of quotas in the next reporting period entails an increase in the rate in the next one.
Another feature of the use of quotas is that they can serve as a quantitative (objective) criterion by which the productivity of each employee is assessed. The fulfillment or non-fulfillment of sales quotas makes it possible to identify leaders and laggards and develop appropriate measures (training, mentoring, motivation) to improve sales efficiency. The topic of performance appraisal will be discussed below.
Types of quotas and their distribution
Before assigning quotas, you must first decide what type of quotas they will be. There are three main types:
- quotas related to sales volume;
- quotas based on financial indicators like gross profit or overheads;
- quotas for certain types of activities in which the participation of sales representatives of the company is expected.
When allocating quotas for sales personnel, a number of factors must be analyzed and balanced, including the potential of the territory, the motivational component of the quota for each employee, the long-term goals of the company, and the impact of quotas on short-term profitability. Since sales quotas are the most widely used, they will be discussed first.
Sales quotas
This type of quota is based on the volume of sales (in quantitative or monetary terms) and is widely used in many companies. Its widespread use is due to the fact that sales quotas can be easily linked directly to market potential, and they are reliable and understandable for sales personnel who will have to put them into practice. Moreover, setting quotas for sales volumes is ideally consistent with the idea of sellers about their profession.
As already mentioned, it is customary to set quotas for sales volumes in monetary terms, in the number of goods or in points. In the latter case, for a clearly established amount of money, number of units or weight equivalent (kilograms, tons) of a particular product sold, a certain number of points is awarded. For example, for every 100 rubles. sales of product A can be awarded three points, product B - two points, product C - one point. Similarly, for each ton of steel pipes sold, five points are awarded, and for each ton of rolled steel sold, only two points are awarded. The cumulative sales quota for each employee is the number of points that he has to earn in a certain period.
Companies use sales quotas when they need to focus on a specific product line, promote sales, or attract new customers. For example, to encourage sales reps to market new products more actively, sales of a new product may earn more points than sales of an old product. The same approach applies to customer service, where you earn more points for the volume of sales (in monetary terms) to new customers than for sales of the same volume to existing customers.
The point system allows you to develop quota systems that stimulate the achievement of certain (important for the company) goals and find understanding and support from sales staff.
Establishing quotas for sales volumes
In the simplest case, the distribution of quotas occurs on the basis of indicators for previous reporting periods or the average sales volume for a given territory for a certain calendar period. At the same time, the staff is morally or financially motivated to exceed past achievements. The attractiveness of this scheme is its simplicity and low cost. In addition, it is understandable to sales representatives.
However, this approach does not always take into account changes in market conditions, such as an increase in sales territory, the emergence of new potential buyers, and the possibility of higher than forecast sales. At the same time, the company may miss out on huge opportunities only because of the lack of an assessment of the market potential. On the other hand, the aggressive policy of competitors or the unfavorable market situation will make any increase in quotas inappropriate. Another disadvantage of setting quotas solely on the basis of previous period performance is an undesirable model for sales personnel. For example, a sales employee who managed to fulfill his quota before the end of the reporting or calendar period can postpone the placement of existing orders until the start of a new period. Thus, he kills two birds with one stone: firstly, he secures a lower quota for the next period, and secondly, he prepares the ground for its implementation.
To distribute quotas for sales volumes for individual regions, you can use the assessment of the potential of the territory. Here, too, one should not be guided solely by numbers, but analyze the market conditions characteristic of each territory with the involvement of sales representatives working in it. But at the same time, it is necessary to take into account the duality of the situation: on the one hand, sales employees are well versed in the specifics of sales in a given territory, and on the other hand, the established quota is directly related to the assessment of the effectiveness of their work, so they can deliberately underestimate the sales potential in order to secure low quotas for themselves. that they can do without too much effort.
Financial quotas
The use of financial quotas allows you to plan the activities of sales staff with an emphasis on the profits and costs of the company. It should be borne in mind that usually merchants first of all try to sell goods that are easier to sell, and pay more attention to those customers with whom it is easier to negotiate. At the same time, it often turns out that the production of easily marketable goods is expensive, and their profitability is relatively low; Pleasant customers do not always make big deals and bring the company not so high income. The establishment of financial quotas aims to focus the activities of the sales force, firstly, on more profitable products, and secondly, on working with customers with high potential. The development of financial quotas is usually based on gross profit, net profit and selling expenses, although in principle almost any financial indicators of the organization can be used.
The disadvantages of using financial quotas are primarily related to the complexity of development and the influence of external factors. For example, the profit generated by the activities of a sales employee is often influenced by many factors beyond his control: the behavior of competitors, economic or social factors, the pricing policy of the company, etc. In such circumstances, many experts consider the use of financial quotas inappropriate.
Establishment of financial quotas
Distribution of financial quotas is made taking into account the financial goals of the organization. Suppose a company sets the goal of achieving a certain profitability for all sales in a particular territory, having two types of products in its arsenal: product A with a profitability of 30% and product B with a profitability of 40%. The activities of the sales department should be distributed in such a way that the overall profitability is 37%. To do this, sales staff must comply with certain proportions of sales of both types of products.
Quotas for certain types of activities
In their activities, sellers perform, among other things, functions that do not lead directly to the sale or the conclusion of a transaction. These functions include, for example, contacting potential buyers, product demonstrations or window dressing. However, these actions set the stage for future sales. The practice of setting quotas only on sales volumes is tempting to neglect functions that are not related to the immediate sale. If a company is customer-oriented, then its salespeople should not neglect such ancillary activities and the company should take them into account when developing a quota system. Here is a sample list of helper functions.
- Contacts (visits, calls) with potential buyers.
- Sending written (fax, e-mail, regular mail) offers to potential clients.
- Demonstration of goods on the spot.
- Contacts with customers for maintenance or installation of equipment under the control of the supplier.
- Organization of exhibitions, conferences and preparation of joint meetings.
- "Resuscitation" of former clients to replenish the ranks of existing ones.
Setting quotas for activities
Before assigning quotas to activities, an analysis should be made of the types of activities required to effectively cover an area, since quotas are related to the size of the region and the number of existing and potential customers that the sales representative will contact. Also important is the category (small, large, key) of customers and their service requirements. Such an analysis will show the types of activities typical for a sales employee in a given territory, and the number of certain actions (visits, calls, presentations) that he needs to perform in the process of working with customers. The sources of information for the analysis are the reports of the sales staff and the research of this market segment, primarily its potential.
Determining the number of employees in the sales department
One of the important tasks of planning the company's sales department is determining the number of sales personnel. The sales department is considered one of the most productive, but at the same time one of the most expensive assets of the organization, so the question of the number of sales personnel should be decided taking into account all factors related to sales. On the one hand, an increase in the number of employees contributes to an increase in sales volumes, and on the other hand, it leads to an increase in the cost of their maintenance. The correct calculation of the need for sales staff is vital to the success of the organization.
Different methods are used to determine the number of sales staff in the field, we will consider the three most common:
- breakdown method;
- workload method;
- increment method.
Stakeout method
This is the simplest method, in which each average sales employee is treated as one salesperson with a certain measure of labor productivity. Therefore, to determine the number of sales force, you need to divide the organization's total projected sales by the estimated sales of each sales employee:
N is the number of sales personnel required by the company;
S is the projected sales volume;
P is an indicator of labor productivity of one seller.
Thus, if a company has a sales forecast of 100 million rubles. and each seller, according to the forecast, can sell goods worth 5 million rubles, then she will need 20 employees.
Despite the apparent simplicity and convenience of the partitioning method, it can be difficult to apply it in practice. First, it uses the reverse logic, i.e. the calculation of the number of personnel is a consequence of the assessment of sales volumes, while the number of sales employees should be one of the initial elements of strategic marketing. Second, the seller's productivity assessment does not take into account differences in the skills of workers, in the potential of the markets they serve, and in the level of competition in different regions. Third, the breakdown method does not take into account employee turnover, and new and inexperienced employees can rarely match the sales of experienced employees. Of course, the calculation formula can be modified by adding a staff turnover indicator to it, but then it will lose in simplicity and conceptual attractiveness. Finally, the most important drawback of this method is that it does not take into account profitability. Sales are considered not as a means to an end, but as a kind of independent task; the number of sales personnel from a decisive factor in obtaining the planned profit turns into a variable dependent on the projected sales volumes.
Workload method
When determining the number of sales personnel using the workload method (or "Stack Method"), it is assumed that all sales employees perform approximately the same amount of work. The volume of work is considered as a derivative of a combination of three factors: the number of clients, the number of calls to each of them and the duration of work with each. The resulting figure is divided by the amount of work attributable to an individual seller, and get the total number of sales personnel. On fig. 3 shows a scheme for calculating the number of salespeople using the workload method.
Rice. 3. The sequence of determining the number of sales personnel using the workload method
The calculation of the number of sales force using the workload method consists of six stages.
2. Determination of the number and duration of contacts with each client in the category.
3. Calculation of labor costs for servicing all customers.
4. Determining the average number of contacts for each employee.
5. Distribution of time of an individual worker by types of tasks.
6. Calculation of the number of sellers.
Let's consider each of these stages.
Stage 1. Classification of clients by category
Typically, customers are classified based on sales volume, but can also be based on other criteria, such as industry, credit rating, product lines, or sales potential.
Any classification system should reflect the difference in the amount of labor required to serve different classes of customers, and therefore the attractiveness of each class of customers for a given company. Suppose a company has 1,030 customers, which can be divided into three main types (classes).
Class A: large or very attractive - 200.
Class B: medium, or moderately attractive - 350.
Class B: small but still attractive - 480.
Stage 2. Determine the number and duration of contacts with each client in the category
This means that it is necessary to estimate the number of contacts (visits, calls) and their average duration for each type of client. Such an assessment is made on the basis of the opinion of sales managers or after analyzing reports and other formal sources.
Assume that class A clients should be visited every two weeks, class B clients once a month, and class C clients once every two months. The duration of a standard commercial visit is 60, 30 and 20 minutes, respectively. Therefore, per year, the time spent for each type of client is calculated as follows:
Class A: 26 visits per year ´ 60 minutes = 1,560 minutes = 26 hours
Class B: 12 visits per year ´ 30 minutes = 360 minutes = 6 hours
Class B: 6 visits per year ´ 20 minutes = 120 minutes = 2 hours
Stage 3. Calculation of labor costs for servicing all customers
To calculate the total labor costs for serving all three classes of customers, you need to multiply the number of customers by the time costs for the year determined in the previous step. The data obtained is summed up, and the number of hours required to serve all types of customers is obtained.
Class A: 200 clients ´ 26 hours = 5,200 hours
Class B: 350 clients ´ 6 hours = 2,100 hours
Class B: 480 clients ´ 2 hours = 960 hours
Total: 8,260 hours per year
Stage 4. Determine the average number of contacts for each employee
At this stage, you need to estimate the number of hours of work per week for the average salesperson and multiply the resulting value by the number of working weeks per year. Let's say the workweek is 40 hours, and the average employee works 48 weeks a year (including vacations, absences due to sickness, or other legitimate reasons). Thus, the average sales worker during the year works 1920 hours:
40 hours ´ 48 weeks = 1,920 hours
Stage 5. Distribution of employee time by task types
It is clear that not everything goes into personal contacts with customers, but only some part of the seller's working time. A lot of time is devoted to activities that are not directly related to sales, such as writing reports, attending meetings, communicating with customers about service issues, etc. In addition, a significant part of the working time is spent on the road. Suppose that the analysis of the cost of working time of the sales staff showed that it is distributed as follows.
Actually sale — 768 hours/year, or 40%
Non-sales activities - 576 hours/year or 30%
Trips - 576 hours / year, or 30%
Total - 1,920 hours / year, or 100%
Stage 6. Calculation of the number of sales personnel
The number of sales force needed by a company can now be calculated by dividing the total number of hours required to serve the entire market by the number of hours available to one salesperson for the actual sale. Thus, the number of sales personnel of the company is equal to:
8,280 hours / 768 hours = 10.78 or 11 salespeople
The workload method (or build-up method) is a fairly common way to calculate the number of sales force. It is not too complicated and at the same time takes into account the fact that different categories of customers require different time to serve.
However, this method also has drawbacks. Firstly, it does not take into account the reaction of different customers to the same commercial proposals of the company's employees. For example, two Class A customers might respond differently to the same sales rep workflow. One customer can order the company's products even without regular visits from a sales representative. Another buyer will agree to become a client of this company only after the sales representative spends more time on him than is allowed by the standard work schedule. In addition, this method does not explicitly take into account the profitability of the frequency of contact with the client (sales visits), as well as factors such as the cost of service and gross margin for the range of goods purchased by this client.
Finally, the application of the workload method is based on the assumption that all sales people use their work time equally effectively (ie, each sales representative actually devotes 768 hours of personal contact with customers). However, it is not. Some employees spend more time communicating with customers, others less, but they use it more efficiently. Small area salespeople spend less time traveling and more time selling. The extension method does not allow taking into account such nuances explicitly.
increment method
According to the incremental method, the number of sales personnel should be increased as long as the increase in profits provided in this way exceeds the increase in costs.
The incremental method is based on the belief that an increase in the number of sellers leads to a decrease in the profits brought by each of them. For example, if one additional sales staff member generates sales of 3 million rubles, then two additional sales staff members will bring only 5.5 million rubles. The increase in sales provided by the first seller is 3 million rubles, the second - only 2.5 million rubles. Therefore, hiring a third employee will provide 2.25 million rubles. new sales volumes, and the fourth - 2 million rubles, etc. An increase in the number of sales staff by four salespeople will lead to an increase in sales by 9.75 million rubles. Keeping in mind that each subsequent employee brings less profit, and the company incurs fixed costs (salary, commissions, travel expenses, etc.), the sales staff can be increased until the profit from the next hired employee equals the cost of hiring him and content.
The incremental method seems to be very convincing, and its provisions are consistent with empirical evidence that an increase in the number of employees can lead to a decrease in profits. However, the decline in profits may be due to other factors, such as the number of buyers per seller, the number of sales visits to each client, the actual time spent by the seller in personal contact with the client, and the design of territories (which will be discussed in more detail in the next section).
The main disadvantage of the increment method is its complexity compared to the two approaches discussed above. If the costs of attracting an additional seller can be estimated quite accurately, then the expected profit cannot be estimated in such a simple way, since it depends on many factors. Here it is necessary to take into account the expected additional income from the activities of the new seller, which depends on the design of sales territories, the distribution of personnel in these territories and the labor productivity of each employee. The calculation is also complicated by the fact that the profitability of the sales department also depends on the company's products and their profitability.
Sales area design
The number of sales territories and their design scheme should be considered as interrelated and interdependent decisions. However, you must first determine the number of sales territories, and then focus on their design.
Ideally, all sales territories have the same sales potential and volume of activity for each seller, which ensures effective outreach. With equal potential, it is easier to evaluate and compare the productivity of each employee of the company. (See the next chapter for evaluating sales force performance across distribution areas in more detail.) Workload leveling improves morale among salespeople and eliminates strife between management and subordinates. Although in reality it is difficult and unlikely to create the same conditions for everyone, when designing sales territories, care should be taken to ensure that all employees are given equal opportunities.
The design process includes six stages.
1. The choice of the basic unit of formation.
2. Assessment of the market potential.
3. Formation of hypothetical territories.
4. Workload analysis.
5. Correction of the boundaries of hypothetical territories.
6. Distribution of sales personnel by territories.
Stage 1. Selection of the basic formation unit
The basic formation unit is a relatively small territorial-administrative area used to define marketing territories (for example, a city or a district). As a rule, preference is given to small formation units, since larger ones may contain regions with different sales potential. This makes it difficult to identify the true sales potential across the entire sales area. In addition, having small oblasts as a base unit makes it easier to adjust sales territories if the need arises, as it is much easier to reallocate customers within a raion than at the oblast or krai level. Usually, cities, districts, and regions are used as the base unit.
Cities. Historically, when the lion's share of the potential of the market was concentrated in large cities, it was a very suitable option for a basic unit. But at present, large cities are ill-suited for this role. In terms of sales, the suburbs and the immediate vicinity of large cities have a potential that is not lower, and sometimes even higher, than the city itself. Therefore, many companies that in the past used large cities as their base unit have now moved to broader classification systems.
Oblasts usually correspond to the administrative-territorial structure adopted in the country. In the region there is usually one large city - the regional center, and smaller settlements. Areas are convenient base units because they have a relatively small area, which makes it easy to adjust sales areas during the design process.
Regions are large administrative-territorial areas, including several regions. The presence in the region of large industrial enterprises, raw materials or human resources or specialization in a certain type of activity becomes a determining factor in the demand potential. Accordingly, there are several large cities on the territory of the region, sometimes with different specializations (industrial, mining, agricultural, etc.) and, consequently, with different population distribution and marketing potential. Changing the sales territories at the regional level is a rather difficult task, since it leads to a significant increase or decrease in the number of customers and the volume of sellers' activities.
Stage 2. Evaluation of the market potential for each basic formation unit
The assessment of the market potential for each base unit is carried out using the methods described at the beginning of the chapter. If a relationship can be established between the sales volume of a given product and some other variable (or variables), then this variable can be used to estimate the sales potential for each basic unit. However, in this case, you need to have a large amount of data for each variable. Sometimes it is possible to predict the potential based on the likely demand from each existing or potential customer in the territory under consideration. This approach is more effective in industrial markets than in consumer markets, because the number of consumers of industrial goods is usually smaller compared to buyers of consumer goods, and they are also easier to identify. In addition, the volume of sales to each client in the industrial market significantly exceeds the volume of sales to the average buyer of consumer goods. Therefore, at this stage, it is necessary to identify the largest consumers, assess their likely demand, summarize individual estimates and obtain a rough estimate of the sales potential of the territory as a whole.
Stage 3. Formation of hypothetical territories
After evaluating the potential of each base unit, adjacent territories should be combined into larger geographical entities. Consolidation should take place in such a way as to avoid overlapping areas of activity of sellers, i.e. so that each employee works only in his own territory and extends his efforts to the territories assigned to his colleagues.
The main challenge is to balance the market potentials for each sales area. You should start by taking into account the workload of sellers and sales potential (the share of total market potential that the company expects to receive); these parameters depend on the competition in the market. It is assumed that all sales staff have equal abilities.
All assumptions made at this stage will be corrected at the next design stages, but for now a general approach to the breakdown of territories is being formed. The resulting number of territories should match the number of territories that management previously determined based on the capabilities of the firm. If this has not been done, the number of sales territories should be determined at this stage.
Stage 4. Analysis of the workload of the sales force
Now you should calculate the amount of work of employees required to cover each of the received territories. It is unlikely that at the previous stage it was possible to form territories that are identical in terms of sales potential and workload on sellers. Most likely, the territories vary greatly in terms of the volume of activity that the sales force expects. Therefore, at this stage, you need to assess the amount of work facing the sales staff. In general, it includes the following steps:
- determining the number of buyers;
- selection of criteria for classifying customers;
- calculation of the frequency of commercial contacts;
- determination of the frequency of commercial contacts with each client;
- determination of the total labor costs of sales personnel.
Determination of the number of buyers
To estimate the workload on sales personnel, all customers in a given territory should be counted, starting with the largest. Most often, this calculation is carried out in two stages. At the first stage, the sales potential for each existing and potential buyer in a given territory is assessed. At the second stage, the result obtained in the form of sales potential is used to calculate the number and duration of contacts (visits, calls) with each of the clients. Total labor costs can be determined based on the total number of customers, the number and duration of contacts with each of them, as well as the approximate time spent on activities that are not directly related to the sale, such as moving.
Choice of customer classification criteria
Sales potential, on the basis of which the frequency and duration of contacts of sellers with customers is calculated, is only one of the criteria used to classify customers. There are other criteria; all of them should be analyzed and, if necessary, used along with the sales potential. Such criteria include competitive pressure on a potential buyer; prestige of the buyer; volume and product range of purchases; internal features of the client that affect the conclusion of the transaction. The set of factors that affect the effectiveness of each commercial visit or contact with a client is very individual.
Calculation of the frequency of commercial contacts
The matrix concept of strategic planning proposes to classify buyers (like strategic business units or markets) in the form of a matrix according to two criteria: attractiveness for the company and difficulties in work. The matrix may consist of four (2 ´ 2) or nine (3 ´ 3) cells. On fig. 4 potential buyers are divided into four cells depending on their potential and competitive advantages (or disadvantages) for the seller company. Each quadrant provides for a different frequency of commercial contacts with customers. The maximum frequency of commercial contacts is expected for customers from cells 1, 2 and possibly 3, depending on the company's ability to take advantage of its competitive advantages. Accordingly, commercial contacts with buyers who are in quadrant 4 will be less frequent.
Rice. 4. Customer Planning Matrix
Determination of the frequency of commercial contacts
At this stage, it is inappropriate to consider all customers of the same category as equivalent, it is more efficient to determine the workload on the seller for each client in all hypothetical territories. To do this, you can use the following method: assign each buyer a score for each of the main criteria and calculate the "index of distribution of sales activities." This indicator is calculated as follows: each of the ratings (“client rating”) is multiplied by the so-called “importance coefficient”, summed up over all factors, and the result is divided by the sum of the importance coefficients.
The distribution distribution index of sales activity calculated in this way reflects the volume of activity of sales personnel associated with making commercial contacts with each buyer. The higher the index, the more contacts the sales staff will have to make when working with this client.
Determination of the total labor costs of sales personnel
After analyzing the clients, the workload for each territory is assessed. It is similar in many ways to calculating the number of sales force in a company using the workload method. The total number of personal contacts is determined by the product of the frequency of commercial contacts for each type of client by the number of clients. The results obtained are summarized and combined with the amount of time it takes to perform (in a given area) non-sales activities. Similar calculations are performed for each hypothetical territory.
Stage 5. Correction of the boundaries of hypothetical territories
The boundaries of the hypothetical areas identified in step 3 should be adjusted to account for differences in labor input required to cover these areas. At the same time, the analyst must remember that the sales potential per client is a variable value and depends on the number of commercial contacts with the corresponding client. The attractiveness of the client for the company directly depends on what attention the company's staff will pay to him. The number of commercial contacts and their duration, of course, affect sales volumes. However, some of the methods used to define workloads by area recognize this interdependence only implicitly.
Stage 6. Distribution of sales personnel by territories
After the final definition of the boundaries of the sales territories, you can proceed to the distribution of sales personnel among these territories. Up to this point, it has been assumed that all sales people have the same abilities and skills. However, in practice there are differences in the experience and qualifications of the staff. The abilities of different employees are far from the same, and there is no need to talk about the same efficiency of their work with the same customers or goods. At this stage, it is necessary to distribute employees - taking into account their personal qualities - across territories in such a way that the contribution of each employee to the company's activities is maximized.
It should be noted that it is not always possible to achieve the optimal distribution of sales representatives. For an established sales structure with established territories and customers, radical changes in territories and customers can be truly catastrophic. Practice shows that in a situation with established sales territories, their redistribution should be carried out gradually, and the changes should not be revolutionary. If the company in its work does not use a clear distribution of sales territories between sellers, then the redrawing of territories will significantly increase efficiency.
The distribution of sales personnel by sales territories should also be carried out taking into account the following considerations. First, redeployment of customers among sales staff can lead to a real decrease in the number or volume of orders. Secondly, the reduction, as well as an unjustified increase in the number of sellers, can also have negative consequences. For example, expanding the sales force means increasing the number of sales territories, which in turn necessitates redrawing existing boundaries, changing sales quotas and reducing potential rewards. Therefore, when reviewing and adjusting sales territories, you need to take into account the views of employees and minimize the damage that can be caused to the relationship between sales representatives and customers.
If all the deals “shoot”, there will be no more deals ahead. The peak of sales is inevitably followed by a failure. But it is possible to predict ups and downs - and it is easy and technologically advanced.
The reason for the failure can be simple: sales managers see the prospect only in the nearest deals. In order for sales to be stable, it is necessary to plan and predict it. And not until the end of the current month, as is usually done. You need a sales forecast for several months ahead.
Technique and technology
Several sales forecasting rules fit on two pages.
- All references to clients that each sales manager has are taken into account in specific amounts. It's not enough to say, "We can sell the site to customer XYZ." It needs to be specific: “We plan to sell a $9,500 business-class website to client XYZ.”
- It is necessary to plan a month when you can wait for the sale. For example: it is now May 2007. And we plan that the site will be sold within two months. So, payment can be expected in July 2007.
- It would be nice to determine (and soberly assess) the probability of a transaction. Each probability has its own coefficient, by which the transaction amount is multiplied to be taken into account in the sales forecast. For example, we divide all expected payments into three types: “guaranteed”, “probable” and “unlikely”. We accept “guaranteed” payments to the forecast with a coefficient of 1: they will almost certainly come. We accept “probable” payments to the forecast with a coefficient of 0.6: the probability of their receipt is more than 50%, but far from 100%. We accept “unlikely” payments to the forecast with a coefficient of 0.1: we hardly expect that this money will come to us.
We sum up the turnovers for the planned transactions, weighted by probability. Separately, we take the amount of expected transactions for the current month (X), for the next month (X+1) and for the month following it (X+2).
- The sales forecast for the current month, equal to the sum of the turnover actually received from the beginning of the month, and the sales forecast for transactions expected before the end of the month.
- The sales forecast for the month following the current one is (current month + 1).
- Sales forecast for the current month + 2.
Usually all this data is driven into the familiar MS Excel spreadsheet format. It makes separate pages for each month, blocks for each of your employees. And formulas are inserted that automatically take into account the probability of payments and issue final forecasts. General, and for each employee separately.
Two things need to be done. First, collect and drive the source data into the table. Secondly, to develop an unconditional reflex among employees: they must take into account all the intermediate results of working with clients in forecast changes. For example, when discussing a contract for a website, the merchant convinced the client of the need to promote the website. For himself, he must immediately assess how the sales forecast will change. What additional amount will the client have to pay for the promotion? For example, $5000. How much will the forecast change? If the trade is "probable", the forecast will increase by $5,000 × 0.6 = $3,000.
Now you can monitor the progress of commercial work based on the sales forecast summary data. It is not the final data itself that is important, but their changes from day to day.
If the sales forecast has not changed compared to yesterday, it means that there was no commercial work.
This is even worse than if the forecast had decreased. A decrease in the forecast means that some deals tried to put the squeeze on it - and they fell off. But the work was still going on. And an unchanged forecast means exactly that no one did anything.
Forecast is already a result
How to determine the optimal sales forecast?
In our case, a technological approach is used to calculate the sales forecast. And this means that the forecast is not taken from the sky and is not sucked from the finger. It is an objective reflection of the current state of affairs on prospective contracts. Therefore, a technological forecast cannot be "optimal" or "non-optimal". It is always an objective reflection of reality. If, of course, it is done correctly.
The only thing that can be clarified along the way (statistically) is the probability coefficients. After comparing forecasts and real sales results for several months, it may turn out that "probable" contracts should be assigned a factor of 0.9. And "unlikely" - a coefficient of 0.15.
Hard implementation
How to get employees to predict and evaluate potential customers?
Disciplinary. Without strong regular management based on technology and standards, the sales forecast will not survive.
How to identify deliberate underestimations in the sales forecast of managers?
First, the manager may underestimate the amount of the expected transaction. This is a “personal threshold” problem. It needs to be mentored. And sales trainings of good practitioners.
Second, the manager may underestimate the likelihood of a successful deal. Well, he can't bet less than "unlikely". If most managers have different deal probabilities, and for some, all deals are “unlikely,” this is clearly seen in the consolidated sales forecast. Such managers have problems with confidence in themselves or in their company's products/services. They need the support of experienced comrades in "boosting" deals.
The most dangerous thing is when negotiations with customers are underway, and customers do not appear in the sales forecast. At a minimum, this means that the manager is engaged in hanging out with clients, and not selling. He does not even assume what exactly he will offer to this client. And for what amount. As a maximum, transactions are diverted to the side.
This situation becomes apparent when a merchant negotiates with clients and travels to meet them. And his personal sales forecast does not change. This situation requires the immediate intervention of the sales manager. And tough decisive action. From joint negotiations to the dismissal of an employee.
How to achieve maximum fulfillment of the sales forecast?
To the greatest extent it depends on the personal efforts of the sales manager. He must constantly monitor the extent to which his employees can ensure the implementation of the forecast for their clients. The rule "no more than one additional attempt" applies here. If the client paid on the appointed day - good. If not, no one cares about the objective difficulties of the client. The employee himself must tell the sales manager the period (small!) for which he will bring this deal to a result. If the deadline has passed, but there is no result, the manager takes over the deal. For an appropriate fee.
Finally, the sales forecast allows you to control the work of the department through several final values. Not only that: how warming the soul of a leader is the very possibility of predicting the future!
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