Business forecasting is a large subject that covers at least, but not exclusively; sales, pricing, quantity forecasts, capital costs, materials availability and valuation. Brightfield encounters the sales, pricing and quantity forecasts the most often.
The sales forecast, which is often the primary challenge, is notoriously difficult and error prone. Errors in sales forecasts ripple throughout the business operations, including both the financial and operating statements.
The sales forecast is the foundation for the financial forecasts. Working capital, short-term financing and EBITDA are just three of the more critical financial results directly impacted by sales forecast errors. Errors that drive increased demand for working capital, stress short-term financing facilities or reduce cash flow from EBITDA shortfalls cause strained or even exhausted financing abilities, putting the business at risk.
The operating statement begins with the forecasted sales and then budgets every headcount and expense item from that foundation. Materials purchases, production capacity, finished goods inventory and even marketing materials supplies starts with the sales forecast. Errors in the business's operating statements translate to excess expenses and lost opportunities.
Simply stated, there are too many moving parts for an easily implemented and accurate sales forecast. Methods that combine historical data along with current market conditions and product life cycles are complex. Simple historical trend analysis is insufficent, but remains the most often used technique. Multiple-tier distribution channels add complexity to the relationship with the customer. Both external market forces and the internal forces such as the ability to execute act on the sales achievement in complex interactions. Brightfield applies multiple analytic processes to the model to surface the best method.
This interactive chart displays the traditional statistical order input forecasts for the dealers in our exammple client's distribution channel. To demonstrate the results from traditional methods, select a dealer from the dropdown box to observe each dealers projections and estimated forecasting errors.Explanation
Pricing is an extremely dynamic forecast even in the short-term. Typical analytical pricing schemes based on stock market models rarely apply in the industrical and technical business sectors because these schemes assume away almost all the forces that impact a vendor. The only possible solution is to model the client's business and determine the role pricing plays in the client's customer relationships. In our client example, pricing is important but held equally important are post and pre-sales services and product capability.
Pricing is made more complex by considerations of the alternative vendors and products, similiarity in fit and function with competitors, customer's dependence on price as a determinant of the purchase decision, time and negotiations between quote and the purchase decision, price promotions and incentives, general levels of market demand, etc. Brightfield's only solution is to test the client's business model using analytical techniques that can include the wide array of factors affecting the customer decision to purchase.
The quantity by part number forecast is one of the most challenging predictions regularly encountered. It is particularly important when long manufacturing cycles, multiple warehousing/staging areas, intense customer support and extended supply chains are involved. Error prone forecasts balloon a finished goods inventory or collapse sales opportunites with stock outages. All forecasts require great care, but forecasting quantity by part number is the most complex.
In business models where the products are available from multiple sources with orders almost immediately placed after the price/deliver quotation, short term fluctuations in demand and availability are most important. In client models where long term customer relationships and multiple quotations are involved the pre-sales customer activity is the most important factor to monitor. Part number quantity forecasts requires the utmost understanding of the client business. Brightfield finds that multiple models and analytics often must be applied to arrive at accurate predictions.
We demonstrate our concept of matching business models with the right analytics using a client example. This example is actually a tutorial on a sales forecasting development when dealers are in the channel. During the application of this process on your site, your staff learns to maintain and enhance the forecasting by daily interaction with us during the development.