Sales Forecasting

SALES FORECASTING Sales Forecast Why forecast? What is it used for? The amount of a product a company expects to sell during a specific period at a specified level of marketing activities Units and Revenue Why forecast? What is it used for? Drives all other budgets All other budgets must wait for sales forecast

SALES FORECASTING Who is affected by it? Ops – raw materials, support for existing products, warehousing, production equipment Finance – inventory, all finance statements and expectations, Wall Street Guidance Marketing – mix variables drive forecast and are effected by it, etc. Sales force – budgets, territory sized and # of reps, sales support, customer service HR – hiring in Ops, Mktg, Sales, all parts of the company, R&D – existing product support, new product investments ($ and direction of investment) All budgets across the company flow from sales budget

Impact of Erroneous Sales Forecasts Functional area Forecast Too high Too low Production excess output, unsold products inadequate output to meet customer demand Inventory overstock understocks Finance idle cash cash shortage Promotion wasted expenditures insufficient expenditures to cover the market Distribution costly, insufficient to sell excess products inadequate to reach market Pricing reductions to sell excess products price increases to allocate scarce products Sales force too many salespeople, high selling costs too few salespeople, market not covered Customer relations money wasted on unneeded activities, resulting in lower profits unsatisfactory due to out-of-stock products Profits lower unit profits since expenses are high lower total profits because market not covered

Qualitative Sales Forecasting Techniques Executive/Owner Judgment Surveys Customer forecasting survey Sales force forecasting survey Expert forecasting survey Delphi technique (panel of experts)

Quantitative Sales Forecasting Methods Averaging Simple averages Moving (rolling) averages Exponential smoothing Time-Series Analysis Trend Analysis Cycle analysis Seasonal analysis

Quantitative Sales Forecasting Techniques Regression Analysis: Predicting sales based on the relationship between past sales and one or more variables Simple Regression: relationship between 1 independent variable and 1 dependent variable (sales) Multiple Regression: shows strength of relationships between multiple independent variables and dependent variable (sales) Caution 1: no one has yet been able to create a formula that guarantees accurate output Caution 2: correlation does NOT equal causation Caution 1: no one has yet been able to create a formula that says guarantees accurate output for inputs A, B, C, and D, (e.g. spending on advertising, consumer promotion, trade promotion and a certain price) and you get output of X sales

Other Sales Forecasting Techniques Market Tests Making a product available in the marketplace and measuring purchases and consumer responses Test full mix on limited scale Search for test markets that look like your national target, but on smaller scale

Assumptive Reasoning (Chain Ratio) Break a problem down into “knowable” parts, then rebuild it using reasonable assumptions for those parts

Market Share-Based Forecast Determine the market size Actual best; potential if actual is unknown Determine the market share you will obtain Excellent justification of share figure(s) “We think…” is insufficient Translate share into units and dollars Market share is after-the-fact calculation; measures success of marketing plan and execution

Forecasting Output Credible case for expected unit sales and revenue figures Credible, not perfect Units first, then revenue Revenue is result of unit sales, not vice-versa Built on well-supported assumptions Every “we think” weakens forecast Market share is “after-the-fact” calculation Typically a poor starting point for a forecast

Forecasting Considerations Multiple approaches often yield best results Use quantitative & qualitative info from all levels Internal information – especially past history National, regional, local information of relevance Competitive/industry information Go as micro as possible – but not to paralysis Localize trends Forecast units and revenue For ALL revenue streams Include returns, lost customers, failed renewals, etc.

Forecasting Considerations Use logic checks/balances Use several forecast methods and compare Logic checks Market share in units, dollars, customers Average sales/day Your own capacity (Ops, HR, etc.) Build flexibility into the plan Watch cash flows by month

Forecasting the “New” Identify and justify a “proxy” How are you the same? How do you differ? Understand environment’s impact on your business Some trends can serve as a directional basis upon which you build Be conservative – better for cash management Credible and believable assumptions Often required, especially with “new” Critical: if they stand scrutiny, forecast is credible Spell out every assumption

Forecast All Revenue Streams Notes Jan Feb Mar Apr May Jun Jul New customers 8 12 16 25 40 35 Initiation fees $1,500 Monthly fees $100 per month Income Statement $0 $12,000 $18,000 $24,000 $37,500 $60,000 $52,500 $800 $1,200 $1,600 Failed renewals -$100 -$200 Total revenue $38,300 $61,100 $53,900

Forecast All Channels Notes Jan Feb Mar Apr May Jun Jul Direct customers 8 38 30 48 60 50 Retail units ASP - Direct $400 ASP - Retail $250 Income Statement Direct sales $0 $3,200 $15,200 $12,000 $19,200 $24,000 $20,000 Retail sales   $7,500 $12,500 Total revenue $19,500 $26,700 $36,500 $27,500

Errors to Avoid Do not just assume revenue in first month Do not deliver straight line forecasts AVOID (or justify) “hockey stick” or “inverted hockey stick” forecasts Try not to apply national trends to local businesses Don’t expect perfection

Market Size (Market Potential) number of buyers in the target market x quantity (units) purchased by an average buyer in the market per year price of an average unit Example 2,000,000 buyers 6 purchases/year $1.50/purchase Based on usage rates Price you get for a unit. Can differ from price customer paid

Breakeven

Costs Breakeven Point The point at which the costs of producing a product equal the revenue made from selling the product The point after which profitability begins Identify in what month you will break even Costs Fixed to Contribution Unit - Per Breakeven Point = Costs Unit Variable – Price Unit Fixed Total Breakeven Point =