Two Ways Retailers Are Overcoming Barriers To Analytics Adoption

Today’s shoppers use dozens of channels and devices to communicate, browse and buy,creating a data trail from every source. But, if organizations have no way to aggregate and analyze this huge influx of data from these savvy connected customers, they’ll never uncover key behavioral insights to more effectively engage them.  And without engagement, they can forget about driving revenue or even retaining customers who expect more personalized experiences.

Retailers recognize the value of big data and advanced analytics but some see adoption of next-generation analytics as too tall an order to fill, despite the success of their competitors. So, why the hesitation, and how can they address it?

Adoption Blocker #1: Culture is the Culprit

From the C-Suite to store associates, there can be strong resistance to change. And becoming a data driven organization requires change … new skills, new roles, and new decision-making processes.

The Solution: Executive sponsorship can provide the commitment, resources and organizational will to build advanced analytics skills in the organization and drive change. For retailers lacking sponsorship, illustrating the benefits of data discovery and big data analytics to support corporate strategies and drive measurable business value can help win executive support and buy-in.

Discussing the “Art of the Possible” using real world, common examples of competitors’ results can also get the conversation started:

• In merchandising, optimizing prices throughout the lifecycle of products can minimize margin erosion.
• Demand forecasting models can improve ordering, replenishment and allocation, resulting in fewer out-of-stocks.
• Marketers, working with the advanced analytics team, can identify new customer segments to target and ensure that customers receive the most relevant content or offer for them.
• Predictive analytics can help identify customers most likely to respond to certain messaging or offers.
• Customers’ search behaviors can be used to improve website search results, boost conversion rates and increase online sales.

Adoption Blocker #2: Stage Fright

Once organizations decide to move forward, they often shuffle their feet. What will it really take to be successful?

The Solution: Stage fright can be overcome by ensuring four key components are in place:

1. The right team – Teams should ideally possess both business and analytic (data science) skills. Business knowledge brings better understanding of impact and interpretation of bottom-line, business results. Analysts can conduct predictive modeling, data mining, and devise statistical methods. If internal skills are lacking, retailers can also leverage consultants to fill any immediate gaps while assisting the team in developing stronger skills.
2. The right tools and technology – Next is technology; the data, technology platforms and analytic tools to acquire, store, explore and analyze both transactional and new data types. Keep in mind that there are many analytic tools available and one size doesn’t fit all, so retailers should consider overall objectives and team skillsets to choose best options.
3. A culture of innovation – Innovation must be treated as a true business discipline of the analytics team and actively encouraged, practiced and recognized. The ability to explore a hypothesis and either “fail fast” or uncover valuable insights that can be operationalized is a core tenant of an advanced analytics team.
4. Integration of new analytic capabilities into operations – Often there is a well-defined technology process for “productionalizing” new analytics, but it’s equally important to integrate them into the business. This includes communicating changes, integrating them into business processes and delivering the appropriate reporting or scorecards to measure ongoing value.

What It’s Worth

Big data and advanced analytics are a huge opportunity for retailers – and one which should never be shelved due to vincible adoption blockers. Having the winning combination of skilled team members, technology and tools, and a culture of acceptance and innovation can help ensure that any organization has the capabilities to effectively dive deeper into their data to interact with today’s connected customers.