Eight times a year, the Federal Reserve prints the Summary of Commentary on Current Economic Conditions by Federal Reserve District—better known as the “Beige Book” for the color of its cover.
In a world awash in data, what is the purpose of “anecdotal information on current economic conditions in its District through reports from Bank and Branch directors and interviews with key business contacts, economists, market experts, and other sources”? Patrick Harker, president of the Philadelphia Federal Reserve Bank, put it best: “Survey data is historical, while anecdotes give you a trend and insight to future.”
For example, the New York District noted that retailers are unable to push through price increases, but Broadway theater tickets may rise 20 percent, indicating a split in consumer discretionary spend and a subtext for inflationary changes. This sort of outlook may be too small to show up as a trend in the data.
Ken Fick, president of FP&A Expert, likes to say there is value in “fuzzy data,” and that information that is just slightly unstructured, perhaps unexpected, and resides just outside of the normal course of gathered data. He sees three challenges with relying solely on the data sets that appear regularly on the screen at your desk:
- Being overwhelmed by the quantity of data. “People may become paralyzed by the fact that all data, regardless of source, will be inaccurate to some degree or another,” he said. “Managers need to weigh the informational priorities of accuracy, timely and relevant information to make the best decisions.”
- Keeping a wide lens on the world. “Informed decision making requires the analysis of multiple sources of data from both internal and external sources,” he said. The data that feeds into our set reporting structure is the result of a data funnel that reflects what was important at a certain time—data is curated from various sources, validated, and fed through production systems to make use of tools and work flows. But what information exists just outside of those proscribed data sets? What new information should be explored and considered for entering into the data engine?
- Data is open to interpretation. Data is often thought to be agnostic, but process of selecting data and compiling the rules to convert into KPIs can contain errors or bias. For example, the International Monetary Fund was roiled by a controversy in which data and indices were manipulated to punish a country. Anecdotal data provides another way to view and test your data sources and existing assumptions.
Anecdotal information—let’s call it “Beige Data”—is all around us, yet it requires the extra effort of searching it out because it is beyond the periphery of where we work. And just like Fed economists, we need to look into the markets for stories that reflect trends. That may require FP&A professionals to enter the market themselves, or converse with those who are in the market and curate their observations to create a dialogue with our business partners about how business is going, what they are seeing, and what is happening outside the spreadsheets and EPM tools. This requires us to comb our data, and also to look up and around.
Finally, Beige Data reminds us that the data funnel that feeds our data management systems should be periodically reevaluated for relevance. What new information exists? How are we using data science to explore meaning of new inputs or correlations we have not previously considered? Then, how should we change the data that is in production or “industrialized” through reports, decision engines, and automation. This is a process best practice that will also contribute to the validation our models and key metrics.
Bryan Lapidus, FP&A, is a contributing consultant and author to the Association for Financial Professionals. Reach him at BLapidus@AllegianceAG.com.For additional insights on FP&A, subscribe to the AFP monthly newsletter, FP&A in Focus.