Complicated Excel workbooks. Invalid and incomplete data. An inability to operationalize the forecast. Does this sound like your organization?
If so, you’re not alone. Many mid-market manufacturers and distributors struggle due to a broken or only partially useful forecasting process, making supply chain and inventory carrying decisions based on bad data, or providing projections to internal or external stakeholders that lack basis and rigor.
Even worse, you may require significant time, meetings, and spreadsheet gyrations to prepare your forecast that, ultimately, only provides information that’s reactive at best.
While no sales forecast is perfect and there is no “one-size-fits-all” approach, there are fundamental best practices and technology-enablers that can meaningfully improve the quality and usefulness of your forecast.
Sales forecasting: Opportunities for improvement
Forecasting doesn’t need to be difficult or confusing. Here are four tips to improve demand planning.
- Start with people and processes. Before technology is considered, it’s important to blueprint and assess your processes for tracking sales opportunities, maintaining a pipeline, combining qualitative and quantitative analysis, and working cross-functionally. Sample best practices include appropriately weighting third-party data sources, standardized deal-tracking, robust product family classification setup, and a right-sized sales and operations planning process. With your sales, supply chain, and accounting teams on the same page, forecast development and maintenance becomes more useful to the entire organization.
- Integrate the appropriate technologies. Struggling to determine which platforms and technologies to use for your sales forecasting process? Oftentimes, the answer is more than one solution. For example, ERP might be the source of historical shipments and sales data, while CRM might contain your sales pipeline. Harmonizing these data sets, performing statistical analysis, and modeling and visualizing the forecast might take place in a business intelligence tool. Potentially, your ERP has a robust, native forecasting module. In any scenario, it’s important to document your system requirements, evaluate the capabilities and limitations of different solutions, and develop a systems strategy that supports the forecasting vision.
- Use robust statistical analysis and models. Sales forecasting is both an art and science, and the science aspect should take full advantage of modern advances in business intelligence and powerful software. Robust tools embedded in Tier I (e.g., SAP S/4HANA or Oracle ERP) or select Tier II ERP solutions, as well as native budgeting and forecasting tools such as Anaplan, can provide multiple models to leverage. Exponential smoothing, historical moving average, and regression analysis may seem like foreign concepts to you today, but can be more readily applied and tested with the right tools. A proper forecasting system should be capable of running multiple models and generating recommendations based on historical accuracy.
- Leverage the forecast in operations. Forecasting is best when it’s collaborative, regularly discussed, and used to drive business decisions. Find ways to publish the forecast so that it’s easily and readily accessible to everyone. Your tools should allow users to leave comments or have threaded communication on the forecast. Also, make sure the forecast is refreshed regularly to make comparisons with actual performance. To the extent possible, leverage the forecast and demand plan downstream for supply planning and replenishment decisions.
While the future state can be bright, it’s a journey to realize the benefits of enhanced forecasting. Improving processes and selecting the right technology for your business along with ensuring successful implementation are critical to circumvent any project failures. If you’re interested in getting more value from your sales forecast, or are unsure where to start, give us a call.
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