In a data-driven culture, all associates, from number crunchers to novices, make strategic and tactical decisions based on data. Today, although 96% of companies report successful business outcomes from data and AI initiatives, just 24% of companies have fostered truly data-driven cultures. In the CPG industry, certain strengths of retail and consumer data can actually contribute to this disconnect. 

Manufacturers can measure product performance in more detail across more channels than ever before. However, accessing, understanding, and interpreting large quantities of sophisticated data can be intimidating for the average associate. So data literacy tends to remain siloed within a single department or among individual experts, while the majority of associates only scratch the surface of what it can do for them in their daily work. 

To foster a truly data-driven culture, the question becomes: How can you make it simpler for your teams to make data-driven decisions, faster and more easily, regardless of expertise?

Lead by example

Companies with winning data-driven cultures have data-minded leaders. In these organizations, whether they’re legacy CPG brands or native digital newcomers, fact-based decision-making is not only encouraged, it’s expected. 

Executives can influence associate attitudes toward data by taking the first steps to driving adoption of data and analytics software, modeling data-driven decision-making in daily work, and consistently communicating the benefits of new ways of working. Data-forward behaviors from leaders have trickle-down effects; because associates want to communicate effectively with leaders, they adopt the common data language. 

Before execs can lead by example, they need to address a frequent barrier to better decision-making: access. It’s impossible to make significant shifts in your data culture if access to (and understanding of) data are limited to a few individuals, teams, or data partners. Advanced tools and technology can free your data from its organizational silos so associates have the information they need in the moments they need it—which leads us to the second point. 

Streamline data processes

Today, the process of requesting and acting on insights requires a lot of waiting. 

A category manager preparing for a last-minute retailer call, or a marketing director seeking a specific actionable insight, might wait hours or even weeks for analysts or data partners to collect, clean, analyze, visualize, and translate data into recommendations. 

These processes are becoming increasingly unsustainable in an age of rapid acceleration, in which retailers expect manufacturers to react to consumer behavior changes in real time.   

Companies are shifting this paradigm with the help of technology. Data and analytics software automates the most time-consuming portions of the insights process, such as selecting, visualizing, and interpreting data. Analysts who would normally spend anywhere from a week to a month scoping and preparing a single analysis can reclaim those hours, and reinvest them in spotting trends and insights to act on. Modern digital platforms can also provide a more user-friendly experience for a businessperson than highly technical tools designed for analysts. With direct, centralized access to data in a digestible format, associates have one less barrier to consistent data-based decision-making.    

Provide associates with a data guide 

The final step to driving your data culture forward is to enable employees to easily extract meaning from raw data. When data knowledge is limited, insights and opportunities stay locked in your database. 

However, the level of sophistication and sheer amount of retail and consumer data available to associates can be overwhelming, so many stick with basic KPIs or familiar, static reports. While metrics such as sales, share, and penetration are certainly important, it’s equally powerful to be able to interpret rates of sales or loyalty rates, and more, when making a marketing or trade decision. 

Companies with data-driven cultures enhance data literacy so that more people can answer common questions around what’s happening in their category, and why. This doesn’t mean that firms must turn businesspeople into analysts. They simply need to be given the right tools. Intuitive automation technology can act as a guide, eliminating one of the most intimidating aspects of deriving insights from data: How to formulate a strong analysis that leads to smart decision making and growth. With automated guidance, associates can select their business question and find answers in minutes, or see the total picture of category performance by following pre-set analytical frameworks. 

Guided analytics technology gives business associates greater self-sufficiency, which then allows formerly time-strapped data experts to take their own analytics to new levels. When associates can answer their most common data-related questions with a few clicks, analysts are then free to dig deeper into large quantities of data, and evaluate it from new angles.