How do you take all the theory that’s been developed and translate it into building a large, rapidly-growing, and highly profitable business? How do you bring that change into your organization, using available tools and analytics? I see these five enablers to becoming a data-driven organization.
Focus on Smart vs. Big Data
You have to identify the most powerful data sources for your key business drivers. Start with your business needs. Do you need to acquire new customers through customer acquisition? Do you have a lot of customers but need to increase engagement? Forget about big data. Get smart data — an example of smart data is cleansed transaction data.
Businesses that take data seriously capture their sales data, in a privacy-safe manner, to understand and answer these business questions. For example, how can you encourage customers like Gary to pick your store over competitors? Or spend more every trip to the store? Construct a loyalty database so that you know when Gary comes back the second, third, or eighteenth time. Don’t look at Gary demographically (male, certain age, two kids, house) but instead focus on his purchasing behaviour, his smart data.
Leverage Flexible, Low-Cost Storage Technology
Four years ago, companies spent millions on big boxes to store our data. Now, taking advantage of cloud technology, there is an incredible increase in processing power at a fraction of the cost. You can now store the global transaction data for the biggest banks on the planet on very basic commodity hardware. Cost should not be an obstacle for any company.
As you identify and store the data that will drive your business, you can also access and store third-party data that you can then use to correlate with your performance. It may be weather data, demographics, or other local data on the competition. Leverage the flexible, low-cost cloud technology that’s available and that can be set it up in just a couple of days.
Use Broadly Accessible, Embedded Tools to Democratize Analytics
If people in your organization are all using different analytical tools — if there is no consistently used and embedded tool — each department will have its own return on investment. And it’s very likely that marketing and finance will also have different points of view!
A central analytics team ensures that someone has the expertise to work with the various business units. They can promote the understanding that different business units will have different levels of maturity, and then adapt accordingly. A central team also helps democratize data use and analytics. Business units now can go to that team and say, I want this, so how do I get started?
Make Decisions Based on Data, Not Intuition, Starting at the Top
A couple of years ago, The Economist surveyed executives and found that 73 percent trust their intuition when it comes to making decisions. These executives hesitate to accept counterintuitive results and do not always trust the data. That is why a consistent analytics platform is so important: if you have consistency and an arbiter that says, “This is the ground truth,” you can help address the issue.
To move from intuition to data, executive buy-in is essential. When you receive monthly briefs, quarterly investment reviews, or requests for large amounts of funding, decision makers must demonstrate the data-driven approach: ask the questions and demand the analysis. Institutionalize a consistent approach. To the executives, I say, “We acknowledge your bias towards intuition, but fight it!” Be an evangelist and a role model.
Strengthen Your People and Processes
You can have the best analytics, the best data, and the best people, but if they cannot work together and share accountability for results, you inevitably will underperform. An excellent framework for this is the book The Five Dysfunctions of a Team by Patrick Lencioni. It describes the key dysfunctions that can inhibit a team from effective interaction, including productive conflict. The first dysfunction is the absence of trust. Next is the fear of conflict. The combination of the two is a lack of commitment. If your teams exhibit any of these dysfunctions, you have a problem. It’s as if you’re in a band of five performers each playing a different song versus five of you playing one great song together.
Over the past few years, one of the big lessons for me had absolutely nothing to do with data, analytics, or technology. It had to do with interaction and the need for productive conflict on your team. A team that works together and does so in a respectful, trustful way gets the best ideas coming up to the surface. That is what will make you a high-performing organization.
