“Don’t tell me how hard you work. Tell me how much you get done.”
– James Ling
Any runner will tell you, the last mile in any marathon is the hardest. The same holds true for analytics. Seventy percent of enterprises recognize that smart use of analytics is a critical strategic priority, but only 10% believe they’re even coming close to achieving the full potential of analytics. The reason for that huge gap can be found in that all-important, ever-challenging last mile.
The last mile is the point at which your front-line employees interact with your analytics and use it to inform their decisions. It’s turning insights into outcomes.
Failure to plan is planning to fail
Chris Brahm, who leads Bain & Company’s global Advanced Analytics practice, says the area they see most companies struggling with is the last mile of analytics. That struggle creates an enormous gap between analytic output and changes that create value for the enterprise. It’s in that last mile that many analytics strategies, no matter how great, end up failing.
“Your analytics project is a failure if it’s not successfully deployed to and used by your front-line employees on a regular basis. And by regular, I mean daily, if not hourly.” – Roman Stanek, founder and CEO of Good Data
A Bain & Company survey of 334 executives found that over two-thirds were investing heavily in Big Data – 40% were expecting a “significantly positive” impact on returns and another 8% predicted “transformational” results. Alarmingly, however, 30% of these executives lack a clear strategy to embed that data and analytics into their companies.
So, how do you close the gap? Make the last mile your first priority.
Maybe it’s the term, “last mile” that makes people treat it as an afterthought, but the reality is, the endpoint of your analytics journey needs to be what drives your strategy before a single data point is collected.
The most successful companies use the last mile to plan the whole marathon. A recent McKinsey report found that 90% of the organizations significantly outperforming their peers devote more than half of their analytics budgets to conquering the last mile.
Based on that same report, McKinsey advises that the key to overcoming the last mile is embedding analytics into decision-making processes. The first step is to make analytics user-friendly, accessible and customized to the groups that will be using them (store managers, lab specialists, et al).
The second step is often more challenging: embedding analytics-based decision making into the corporate culture. Companies must seek to create and foster an environment where analytics are embraced as essential tools that inform thinking and augment judgments. This must be a systemwide change, adopted by everyone from front-line workers to the C-Suite.
Empowering Your Front Lines and Encouraging Collaboration
We already know management is on board, now the key to successfully turning analytics into outcomes is enabling your front-line employees to leverage analytics in their decision making. McKinsey found that breakaway companies are 1.5 times more likely to report that their organizations “have achieved quick, continually refined decision making through analytics, one of the keys to the last mile.”
“Here is one example of what this allows companies to achieve: a major retailer saw a significant increase in sales by delivering demographic data on customers to store managers on a daily basis and empowering them to act on the insights the data provided (for example, penetration and shopping frequency by demographic segment in the trade area of the store).” – From McKinsey Analytics, Breaking Away: The secrets to scaling analytics
The report also found that nearly 60 percent of breakaway companies utilize cross-functional teams made up of business representatives, analytics translators, UX design experts, data engineers and scientists who work together on agile teams. The diversity of membership in these teams mitigates the risk of creating isolated silos.
Building an Analytics-Integrated Ecosystem
For analytics to reach its true potential, it needs to be a driving part of every step; it needs to be pervasive throughout your organization. For that to happen, the experience of utilizing said analytics has to be seamless.
As anyone who has ever worked on an innovation endeavor will tell you, getting workers at any level to adopt change is a massive, often frustrating undertaking. People are often averse to change in their jobs. They are busy and learning a new program/step/protocol is one more thing on their plate that many, especially in large, enterprise style organizations, view as a headache and nothing more.
Facilitating cultural level changes within your organization requires buy-in from the top-down and action from the bottom up. One of the best ways to get that second part off to a great start is to make sure whatever tools or protocols you are asking users to learn are as simple and intuitive as possible. From API-enabled middleware to intuitive dashboards, recommendation engines, and mobile apps, giving your people the best possible, user-friendly tools to access your analytics can make or break the success of your program.
Start with the Finish
The biggest takeaway from all this is to design all analytics projects with “last mile” adoption in mind. As Bain points out, “The best analytics solutions emerge when data scientists and business stakeholders work together, set success requirements early and keep end-users central to decisions.”
When you are designing and implementing an analytics project, consider the five W’s of how all the data you ultimately collect will be used: Who, What, When, Where, and Why.
Who will be using the data to make daily, even hourly decisions?
What methods and tools will your workers use to leverage these analytics?
When, within the process, will the analytics results become available to end-users?
Where will all this data end up?
Why are you collecting each data point and how will it impact your ability to implement analytics-driven decision making and turn insights into outcomes?
Making the last mile your priority will get you the most bang for your analytics buck and give you a strategic advantage over competitors who are still dumping money into Big Data initiatives with no clear strategy to make use of it all.