Adopting analytics poses a conundrum for most retail companies. Teams need management to rally around the decision, yet, getting management to allocate the people, the time, and the money to analytics can be a tooth-and-nail fight. One misstep in the cycle and it’s easy for leadership to write off analytics as ineffective or not worth the effort.
When it comes to opening the door to retail insights from analytics, management holds all the cards, which means that the wrong approach can bar opportunity. Instead, identify and avoid these common-mistakes during the decision-making process.
Mistake #1: Failing to Consider the Needs of the End Users
One of the biggest mistakes decision makers and management can make is to ignore the needs of the end user. When adopting new analytics solutions, search teams are typically comprised of IT and technology-focused individuals rather than those who will actually use the data. This can lead to the adoption of a solution that is wrong in scope, a process that delivers the wrong types of data, or a process that complicates, rather than simplifies workflow. To capture the desired insights and get the right data into the right hands, it is necessary to bring together a group of diverse users who know which questions need to be answered.
Consulting with end users ensures that an analytics solution meets their needs and increases potential buy-in. When they are able to raise their hands and say, “We need to be able to do A, B and C,” they feel as though their contributions are valued, and, when the solution rolls out, those users will be far more likely to adapt to change much more quickly than they would if a solution or vendor is simply thrust upon them.
Mistake #2: Failing To Plan for Long-Term Scalability
A retailer’s analytics needs today will be markedly different from their needs five years from now. Management can get hung up on the here and now, but in order to determine the right analytics solution, scalability must be a key driver in the decision-making process.
Choosing a solution that cannot grow and change with the needs of the company is a waste of resources. As time passes, more and more data accumulates and retailers want to find innovating new ways to use that data each day. It is a near-certainty that the volume and variety of data that’s collected, stored and analyzed will continue to expand in the next five to ten years, as will the number of ways in which that data is put to work. An analytics solution must have room for growth, allowing retailers to expand storage, modify service levels and increase processing speed on demand. Thankfully, cloud computing facilitates the scalability of big data analytics solutions, giving retailers the option to pay for only the services and space they use, with room to scale up or down as needed. However, not all cloud solutions are created equally. Mangers must be certain that a contract allows for scalability that is as seamless as possible, to ensure agility during periods of rapid growth.
Mistake #3: Following Suit Instead of Meeting One’s Unique Needs
In retail, it’s easy to get caught up in the mentality of “Keeping Up With the Joneses.” Management sees a tactic working for a competitor and they want to hop on that same strategy. The needs of every retailer are unique. If an enterprise-level solution isn’t necessary, there is no need to exhaust the resources to adopt it. Likewise, just because a vendor is new and trendy, if it can’t support the vast analytics needs of the company, it would be a waste to enter into an agreement with that provider.
Management should approach analytics from a needs-based perspective. To settle on the right analytics solution, decision-makers need to consider their unanswered questions about their customers, markets, and employees. Where do bottlenecks occur in workflow and where do gaps exist in their knowledge base? How tech-savvy is their workforce and how will staff adapt to new solutions? What can the budget sustain? What does the organization need to know about its customer base that it doesn’t already know? Assessing current needs and gaps of the organization and tailoring the analytics solution will always lead to better results than hopping on the latest retail analytics bandwagon.
When it comes to choosing effective retail analytics solutions, management is in the driver’s seat. By putting together diverse search teams made up of end users, considering long-term scalability and putting the needs of the company over the latest analytics trends, managers can set a course to succeed with analytics.