Companies will also need to evaluate their automation strategies in production and fulfillment operations to determine where material handling automation and robotics can improve to reduce future business risk. It will be important to evaluate how these potential upstream changes affect the planning and execution processes.
Evolve your approach to analytics
Many traditional forecasting approaches rely heavily on internal historical data — exactly what we are trying not to do. It’s time to move away from one-model-fits-all forecasting into a series of more advanced models that glean insights from both market and internal data. Market impacts are best modeled with data as close to point of consumer purchase as possible. CPG companies can use these consumption models as an input to a better market-driven shipment forecast.
While this isn’t new to retailers, it certainly might be a new way of thinking for CPG companies. POS and syndicated data are often cleaner and more responsive to changing market dynamics than internal shipment or order data. Companies often use syndicated data to understand market opportunities — examining the effect of promotions and merchandising while also gauging trends in distribution. And strategies around these areas are easily integrated into predictive forecast models providing opportunities for tactical scenario planning.
Companies should now determine how their business moves with macroeconomic indicators — especially leading indicators. Look at past business results to model this relationship over time. What are those three or four reliable critical metrics that can serve as a two- or three-month lead? Regardless of whether we enter a sustained recession or the global economy rebounds, this is great information for companies trying to understand the impact to long-term demand.
Executives can leverage early data coming from Asian countries moving into recovery for early insight into consumer behaviors. Some of these early demand patterns may prove useful in predicting consumer behaviors in other geographies.
All these factors can integrate and inform an entire demand management suite of analytics. For example, economic response and marketing factors are realized over time in the ebb and flow of base sales. This is different from promotional models where an added promotion adds immediate volume. These are two different models, but they can inform each other. Multiple models integrating signals on the current state of the business work together to create the best possible forecasts.
Everyone will refine their marketing and sales strategies based on their assessments with fine tuning based on the global economic situation. Further enhance your insight by predicting your competitors’ marketing and promotional behavior. This can inform your own internal strategy and can also feed your forecast models. Evaluate whether competition is following your predictions and, if not, refine your competitive forecast.
Digital intelligence keeps you in tune
Consumer product needs and quantities have changed dramatically since the crisis began. Even the timing and frequency of store visits and online orders are changing. The consequence for retailers and CPG companies is that they can better serve customers when they use more advanced analytics combined with digital intelligence to stay attuned to those changing needs by region, state and location.