Economic metrics: How CPG leaders can craft more accurate forecasts

Consumer Products Writer

The rules of product production, planning and development have changed. In the past, CPG brands have dedicated the bulk of their efforts to mass-market approaches that maximize reach across a handful of distribution partners. However, as consumers are becoming more personalization-driven in their shopping habits, buying landscapes are becoming increasingly fragmented. Thanks to mobile devices, consumers can research competitor pricing and product alternatives, no matter where they are.

CPG leaders need new economic metrics to connect the dots between product planning and consumer behavior. Here are three areas in which big data can help:

1. Costs throughout the entire value chain

A recent report from Strategy& points out that 75 percent of companies in the CPG industry have implemented sales operations and planning programs that improve accuracy in forecasting and planning. Even still, the majority of these companies are benchmarking opportunities based on cross-sectional, rather than comprehensive, views of organizational operations. Strategy& explains that in today's global and integrated value chain, CPG leaders need to trace costs at all organizational layers. The basic idea is that CPG production is a journey that requires trade-offs at multiple stages. Industry leaders need to craft cost-oriented stories around their economic metrics and pay particular attention to customization, delivery to the shelf and supplier impact.

Big data makes this perspective possible. By integrating systems across global operations, CPG leaders can refine their sales operations and planning programs, and then better align varying costs with anticipated demand and ROI forecasts. This level of nuance presents a complete economic picture for new products.

2. Relative and absolute growth opportunities

Emerging economies have presented new areas of opportunity for CPG leaders, but The Wall Street Journal suggests that levels of international demand may be sluggish or slowing down. Over the long-term, however, growth opportunities will continue to expand. The collective gross domestic products of emerging markets will overtake those of developed nations by 2020, according a report from McKinsey & Company.

Decision-makers need to determine how to best allocate their resources over the short and long term, explains the McKinsey report. CPG leaders must continue to forecast and analyze growth patterns. Thanks to big data and financial modeling software, it's possible to monitor both short- and long-term trajectories concurrently, in both relative and absolute terms. Total economic impact

Supply chain operations and profits are only part of the manufacturing and retail value equation. CPG production drives economic activity across most industries. Companies yield tax revenues and employee salaries, and their activities cause spending in healthcare, the restaurant industry and real estate, for example. Product demand stems from all of these channels. Forecasting models and economic metrics must account for a diverse spectrum of CPG stakeholders. The difference between then and now is that today's CPG leaders have access to the predictive modeling techniques necessary to fully quantify total economic impact.

Big data can help by accounting for variations in stakeholder types and assigning weights to different personas and stakeholders in the predictive modeling process. With this perspective, CPG leaders can make both nuanced and macro-level predictions around their production processes, to create more tailored supply chains, distribution practices and marketing initiatives.

Forecasts are crucial to the product planning process. Today's CPG leaders must consider a different set of economic metrics than ever before, as consumer landscapes become more fragmented and new industry stakeholders begin to emerge in the form of governments and industry buyers. These perspectives culminate in a total market perspective that contextualizes value chains within relative and absolute growth opportunities.

How can you maximize the value of your consumer data to personalize your marketing message? Learn more on our IBM Consumer Products Industry Solutions Page.