Go Beyond “Big Data” To Build Accurate Forecasts

Producing accurate sales forecasts is by no means an exact science for retailers. But economic and competitive pressures, fluctuating sales, and dramatic changes in consumer purchasing behavior has made it downright perplexing.

Trying to pinpoint exactly where, when and how consumers will make purchases at any given time makes forecasting even more difficult. On demand services, such as Uber, Netflix and Amazon and social media platforms like Etsy, have changed consumer expectations, buying habits, and preferences. This significant shift in loyalty and behavior is upending both legacy business models and value chains. It’s clear that traditional forecasting methods are being challenged and relying on historical data or quantitative factors alone will not be enough to help retailers develop accurate forecasts.

Getting forecasting right, or at least landing somewhere in the ballpark relative to actual results, is not just critical for retailers, but also essential to their success. Recent headlines involving retail heavyweights show how challenging and unpredictable the environment is: missed revenue projections have led to bankruptcy filings, store closings and declining stock prices.

Three keys to better forecasting

 Producing better forecasts doesn’t begin or end in the data center. The process also shouldn’t rely too heavily on historical data. Rather, the new competitive landscape suggests that retail CFOs combine “Big Data” with other key variables to capture rapidly changing factors in the new environment.

Here are three ways to do that:

1.Shore up internal processes. Simply analyzing spreadsheets and running the numbers up the chain of command is not enough. We need to begin to “flex” our forecasting models and apply more sensitivity and analysis to the data we capture. Draw intelligence from broader internal subject matter experts who are very close to the competitive environment and the end customer.

2.Call on the frontline. There are perhaps no better experts on consumer behavior on your team than the so-called front line—your sales and marketing teams. Focus on their knowledge of purchasing trends and behaviors to capture changes in the competitive market. Leverage their experience to help you understand customer activity and how your competition reacts to them.

For example, Amazon thoroughly understands its audience’s patterns throughout the buying cycle. It uses predictive modeling and intuitive, intelligent marketing to suggest other products of interest to consumers. At the same time, it also offers guardrails around these recommendations to avoid becoming too intrusive to its consumers.

3.Analyze the sales and R&D pipeline. Probe trends and customer preferences. Focus on demographics, changes in customer behavior, customer traffic, the profile of sales (e.g., basket size, merchandise mix) and personas. Seek to understand the influence of digital and social media platforms on your organization and pay particularly close attention to how millennial customers are using them. For example, customers’ “multi-channel” buying habits have prompted many retailers to combine channels, i.e., buy online and pick-up in store offers.

Work with your IT departments to invest in systems that can harness customer insights and respond to them in real time. Customer surveys, particularly those offering discounts as incentives, are an excellent way to conduct research and development and build loyalty in the process.

Starbucks, for example, has a loyalty program and a companion app that not only helps capture customer data, but also “rewards” repeat customers for frequent purchases throughout the year.

To adapt to today’s environment, retailers will need to step up their game by applying and analyzing a robust combination of both qualitative and quantitative inputs from internal sales teams and subject matter experts. This includes digital purchasing trends, habits and preferences—data that was virtually unavailable five years ago—to help them understand their customers and the changing factors in the retail environment.

Those that succeed will be better positioned to manage and lead their organizations, support more strategic decision-making and better allocate and deploy their resources in the future.

John Grund is a partner at First Annapolis where he manages the Retail Services practice.

About John Grund (Partner at First Annapolis Consulting, Inc)

John Grund joined First Annapolis in 1995 and co-manages the Card Issuing practice area where he helps clients develop and execute payment product strategies. One of John’s principal specialties is the formation and growth of financial services partnerships between leading financial institutions and market leaders in the retail, grocery, airline, hotel, automobile, and technology sectors. John and his colleagues routinely advise clients on the development of unique partnership structures involving highly customized marketing, financial, technology, and contractual arrangements. He currently sits on the board of advisors for Vyze.