Businesses run in an environment of change and evolution that has multiple dimensions – Economic, Sociological, Political, Competitive, Regulatory, and Technological. At the very heart of the drive for business success is the customer/consumer demand for the company’s products. Indeed, a company’s revenue is a mirror reflection of said demand and all factors that affect it. Understanding consumer behavior, therefore, is of paramount importance.
Demand for a company’s products and services ebb and flow with a complex mix of seasonal, cyclical, and life cycle effects. As Forecasters and Demand Planners, how do we best structure our forecasting and planning efforts in this fluid and often volatile environment?
1. Gather Information From Market Facing Colleagues
This is to discuss ideas with those who are interacting both directly and indirectly with customers and consumers. We want to explore their experience and thinking regarding why and how purchase decisions are made, and what they think the most important considerations are in the purchase decision process. Marketing, Sales, and Product Management professionals can be especially helpful in their perspectives.
The primary purpose of this is to not only evaluate key factors that may help us to forecast, but to explain the variation in patterns of demand that have been historically experienced. Analytics methods – both qualitative and quantitative – are valuable tools that help characterize and explain purchase behaviors of both customers and consumers.
2. Review Qualitative Inputs
Review the findings from our discussion with our colleagues in Marketing, Sales, and Product Management. This can be a collaborative forum or meeting/s that happen ahead of the formal S&OP process. Organize their insight about sources of demand variation and gain consensus from the various stakeholders. This is a forum for feedback and exploration that can refine the conclusions, challenge our hypotheses, and prevent misconceptions about customer and consumer behaviors.
3. Create Scenario Models
Once we have an understanding of the different demand drivers, we can generate scenario models that incorporate said demand variables. Scenario models help us understand how demand for our products will look in different situations that may arise in future.
For example, we could generate models with unique assumptions regarding periods of economic growth, economic recession, business cycle stages, product lifecycle stages, demographic shifts, population rates of change, product pricing, supply chain issues, business sector consolidation, and more.
Pick the assumptions that are relevant to your business and you’ll have an understanding of what could happen in different scenarios. Adaptation to rapidly changing conditions means that we should not think of purchase behavior from a steady-state or static perspective. We need to have a portfolio of explanatory and forecast models that we can access to quickly pivot and adapt.
It is important that we understand our customers and consumers. We should understand their motivations, needs, purchase decision process, and probable response to changing conditions affecting them. We should create scenarios of behavior under a variety of alternative assumptions.
We should be observant. We should be ready. We should be prepared. The above approach improves the performance of demand forecasts, supporting the company in its efforts to increase operational and financial performance.