Building analytics culture graphsThe year 2011 saw the release of “Moneyball”, starring Hollywood actor Brad Pitt. The film depicted the Oakland A’s coach Billy Beane and general manager Paul DePodesta’s successful attempt to put together a baseball club on a budget by employing computer-generated analysis to acquire new players. One particular scene in the movie mirrors the challenge that most retail organizations face when trying to create and build a culture of analytics: resistance to change. When the characters based on Beane and DePodesta first present their data-driven method of player selection, there is perceivable tension between the newer, stats-based analytic approach and the more subjective one of the older scouts.

Challenging the way things are done in an organization is never easy. Processes have been built over time, and to change these habits is often difficult and potentially destructive. Retail organizations who invest in analytics technology will be familiar with this internal sentiment: there is often resistance to change (in this case, the implementation of a retail analytics system) because stakeholders often feel overwhelmed or lost in the sea of data. Traditional retail managers are still wary of building strategies around analytics. Why?

  • There’s often only a superficial understanding of the Building analytics culture graphscapabilities of the retail analytics system
  • There’s a shortage of skilled analysts and others who might have prior experience of working with retail analytics systems
  • Analytics is still viewed as a concern of the IT division as a data warehousing and management issue, rather than a strategic weapon.

How can organizations drive this change? How can they prepare and organize themselves to imbibe a retail analytics culture?

Follow the leader

Follow the leaderThe attitude of the leadership plays an important role in steering the ship through the choppy waters of analytics adoption. Wal-Mart was one of the first retailers to adopt retail analytics, way back in 1991.They invested $4 billion to create RetailLink (their internal supplier portal and sales database) as well as innovations like bar code readers – long before the competition did. The decision to invest in retail analytics at such an early stage in the game reflects the confident attitude of the leadership towards retail analytics technology. In 2010, Rollin Ford (Executive VP/Chief Information Officer, Wal-Mart Stores Inc.) told The Economist “Every day I wake up and ask, ‘how can I flow data better, manage data better, analyze data better?” This kind of attitude will then permeate through the organization.

Those managers and leaders in the middle ranks who are proactive about developing a fact-based culture should be identified and promoted.

Make analytics a common language

Make analytics a common languageDeveloping analytical capabilities within the organization is imperative. Consider implementing a learning and developmental program that will equip the right individuals with the ability to effectively understand insights provided by the retail analytics system – and don’t limit this training to an ‘analytics’ team.
At, each business group is asked by the IT department to identify who needs access to BI, as well as to classify each of these individuals as either a basic, intermediate or super BI user. Depending on their level of familiarity, these users are given further training. The organization believes in equipping as many employees with analytical and BI skills as possible. According to the CIO, Steve Bozzo,”Our basic goal is that we understand everything we can about our customers, so it’s important to get increased numbers of people involved in BI. That effort cannot hurt as long as they have the appropriate training and can use the tools that we give them.”

Break down departmental barriers

Break down departmental barriersTo successfully build a retail analytics culture within an organization, it’s often important for silos that have been built up at the business group level to be dissolved. Retail analytics requires cross-functional collaboration, and the resulting insights are often used widely across the organization by different departments or functions. For example, office products retailer Staples adopted a new approach to sales forecasting when it decided to take eight million data transactions each week as input from its 1,100 US stores. The resulting integrated forecasts are now used across stores in the US to forecast seasonal sales, schedule labor, manager inventory and replenishment and estimate annual budgets. All these functions are handled by different business units who need to work together to provide the right input data, and they collectively benefit from the result.

Reach out to naysayers

Reach out to naysayersKeep in mind that there will be individuals who will be uncomfortable with the thought of automated processes taking precedence over their carefully honed ‘gut feel’. The way reports or information is presented may change drastically after the implementation of a retail analytics system. This may cause anxiety or may make individuals unhappy with the new process. It is important to consistently communicate the benefits and implications of the retail analytics system to everyone in the organization, so they can be informed about what to expect and how they will benefit. Walk stakeholders through the new changes and how the business will be affected. Make sure you give stakeholders enough time to get accustomed to the new changes.

Retail analytics culture: a strong foundation for your analytics system

As a retailer, investing in a retail analytics system takes up considerable economic resources and time. It’s important to have a strong retail analytics culture to support the system, as this contributes directly to the system’s success or failure. It is this culture that can drive transformative change, and deliver on the full potential of your analytics investments. To ensure that your organization is prepared for the changes and benefits that occur as a result of the implementation of the system, you must ensure that:

  • The organization’s leadership sets a confident and positive example
  • Enough resources with the organization are trained to interpret and respond to analytical insights
  • There is cross-departmental cohesion in using the retail analytics system
  • There is a majority positive stakeholder involvement

Have you gone beyond merely implementing a retail analytics solution to building a widespread analytics-driven organizational culture? Does every level in your organization have access to analytics and do stakeholders across functions know how to use these insights for day-to-day operations? If the answer is ‘No’, it is time you begin the journey today.