There is a common misconception that recruiting an expert in data analytics or data science is going to solve your problems. But often the new talent with data expertise does not have the domain expertise required to fully understand these problems.
Today’s data scientists are highly capable but most have not had “the job” or been directly accountable for results. In the absence of practical experience you don’t know what you don’t know, and gathering and applying the right data to improve performance proves difficult.
Today’s “experts” do not know the questions to ask, what information to collect, and what to discard in order to improve the P&L. Only with experience do you learn how to prioritize and use critical information to guide the decision-making process.
If your goal is to improve gross margin the obvious starting point is reducing cost of goods, increasing price, or reducing markdown rate. But if you dig a little deeper and examine your stock-to-sales ratios, regular price sell-thru, allocation and performance by location / color & size, you may be able to improve your profit without adjusting price, quality, or promotional activity.
With the benefit of experience, you learn what data points are important, how to analyze and leverage them to make smart decisions and improve the business.
You and your business need data analysis expertise, but make sure you marry it with real sector expertise. Ideally people who have had real P&L responsibility, who understand the domain dynamics and can ask the right questions of the data—and help shape and improve decisions that positively impact the business.