Retaining loyal customers, generating turnover and responding to global competition are becoming increasingly challenging. And the current economic climate doesn’t help as financial pillars appear to shake and stumble, draining confidence amongst businesses of all kinds.
In times like these, it is crucial to remain focused. Forecasts are a useful foundation for setting goals and KPIs based on predicted future sales and production, and adjustments to both production and marketing can be made in reviewing forecast figures and actual results.
Forecasts are nevertheless tricky to create as it is difficult to obtain reliable data and it is often impossible to predict the future beyond the short to medium terms. Furthermore, the data gathered can be biased, out of date or flawed.
A recent article in the Wall Street Journal discusses the collaboration of company departments – chiefly the sales, production and marketing departments – in creating forecasts, and suggests seven rules companies can follow to make the most of collaboration in their forecasting efforts. These can be summarized as follows:
- Involve senior executives. Senior executives need to be on board, not only to achieve buy-in to the forecast, but also to approve and action spend on forecasting technologies that enhance the collection and sharing of data. The author suggests:One way to get the attention of key executives is to calculate what a one-percentage-point improvement in forecast accuracy may mean to the company. As supplies come closer to demand, customers can buy more, stores return less, and more revenue goes straight to the bottom line instead of paying for excess storage and handling. For a large company, it could add millions of dollars to the bottom line.
- Explain the mutual benefits. Forecasting needs to benefit all those involved in the data sharing process. The authors argue that whilst salespeople may want to focus on selling and not forecasting, the salespeople would however become interested if they believed that a more efficient supply chain would help make the product available according to customers’ requirements, thereby increasing sales commissions.
- Clearly define goals and agreements. Setting clear goals and metrics are paramount to increasing efficiency, especially of supply chains, such as reducing the number of days of inventory on hand. The authors cite Procter & Gamble as an example: the company uses a scorecard that looks at on-time deliveries and the number of times a store runs out of a product, amongst other things. The goals should constantly be reviewed to eliminate unrealistic expectations between departments and to determine whether goals are met, thereby enabling the most effective changes to be implemented and improvements made.
- Use the best technology. A central database is required to enable different parties to share data, such as sales, inventory and purchasing data (historical and current). The best technologies should be used to capture, store and share this data.
- Focus where revenue and profits are greatest. Since resources are limited, companies should focus forecasts on products that yield more revenue and profits. A deviation from this could result in staff devoting more time to less important and lower value products, rendering the forecasting a wasteful exercise.
- Link incentives to companywide goals. Incentives and rewards should be based on achievements of the company as a whole, as opposed to those of particular departments. This enables effective and reliable forecasting, as opposed to deliberately low forecasting that is set too low with the aim of bettering predictions and therefore making a certain team look deceptively good.
- Aim for continuous improvement. It is crucial to continuously check the data to eliminate any errors that could contaminate the forecast, such as prejudiced assumptions or incorrect benchmarks.
Finally, we would like to add a further tip to successful forecasting. The seven tips above are based on an inside-out approach, i.e. the view from within the company. It would be beneficial to test forecasts from an objective standpoint, involving market and competitive intelligence. For example, market research could be used to create comparable datasets (such as competitor forecasts or market forecasts as a whole), and this can be achieved through desk research, statistical extrapolation, and a select number of interviews with industry experts (such as large customers, trade associations, competitors and distributors).
B2B International USA’s Business Development & Research Manager Julia Cupman says:
Market research offers an independent means of not only verifying forecasts, but also of obtaining invaluable insights into everything that can directly and indirectly affect a forecast, such as challenges facing a market, market trends and influences, strengths and weaknesses of a company and its competitors, threats, unmet needs and opportunities. Hence companies who only base their forecasting and planning on internal knowledge may not be maximizing their full potential.
For more information on forecasting and how market research can add value, including different types of forecasts, the role of forecasts and forecasting methods, please take a look at our white paper: Forecasting and Scenario Planning.