Lessons from the track
What a reluctant but triumphant runner learned about change
By Kimberly Nevala, Best Practices, SAS
Adopting a data-oriented mindset and becoming an analytics enterprise can be daunting – especially for organizations that didn’t inherit what has been termed “analytic DNA” (think Amazon, Google, Facebook and their ilk). But it can be done. My experience with distance running provides some interesting comparisons.
I dislike running. And not a little. Running is hard. Time-consuming. Sweaty. And involves short, tight pants. Which might be OK if I enjoyed the act of running. But I don’t. In fact, I am convinced the vaunted “runner’s high” – that mythical state of synergy at which muscle, lungs and brain just click, everything flows, nothing hurts and you can run forever – is a myth. Created by those who’ve mastered the art to torture those of us who haven’t. After all, have you ever seen a runner smiling?
That said: I’m the proud finisher of a marathon and a half-marathon. How? Why?
I don’t necessarily love the act of running, but I do like the result. The challenge of overcoming a perhaps self-inflicted limitation. The competition. The sense of accomplishment from going beyond what I’m naturally inclined, or ever thought, I could do. But conquering the road didn’t happen overnight. Or by chance. There were a number of important factors at play:
Conscious and unconscious biases, doubts and beliefs grounded in past experience and history can create a powerful inertia and resistance to change. Especially if you’re trying to shift an entire organization toward becoming more analytical in its day-to-day activities. On those long runs with lungs shredding and muscles screaming, deliberately shifting my mental dialogue from “WHY am I doing this?” to “Hey, I AM doing this!” made all the difference in the world. My muscles didn’t hurt less, but my mind was engaged and open to the possibility of success. Call it the power of positive thinking. Or marketing. But time – and thus distance – went by just a little bit faster.
What are the three dimensions of an analytic enterprise? Watch this to find out.
Consciously shifting your perspective before the work begins will lead to even better results. Openly acknowledging that adopting a data-driven mentality will be hard work, but that your organization will not only survive but thrive as a result, changes the game on a level that is hard to quantify. And with each challenge surmounted, the organization’s mental dialogue naturally shifts from “What were we thinking?” to “Of course we can do this. We’ve done it before. What’s next?”
The goal (and a plan to get there)
Going from being a nonrunner to finishing a marathon in under four months didn’t just happen. It started by clearly articulating what I wanted to accomplish and, more importantly, why. And came to fruition through careful planning.
I started by honestly assessing my current state of analytics fitness. Seeking tips and techniques from those in the know. And, last but not least, identifying the training plan (and there are many out there) that best matched my cognitive, physical and logistical needs. Want to develop your organization’s analytic capabilities? The same precepts apply.
Can you run in bare feet? Absolutely. Children do it all the time. Not to mention the folks running around in those strange sock-like, toe-hugging contraptions. Can you run in all-purpose sneakers? Sure. However, the right tools make the process so much easier. A running shoe is purpose-built. I’m convinced that finding the running shoe that fits your particular weight, gait and foot shape is not only good practice but an absolute must. A case in point: I’m a supinator. Even when running I like to be on the outside edge of things. My colleague is a bit more neutral. She runs on pillows. Literally. Her running shoes have cushioned platforms that appear to be a foot high. Could I wear her shoes? Yes. But. My feet would ache, my shins would rebel and the whole undertaking would be just a little bit harder.
Likewise, choosing the appropriate analytic solutions can enable and encourage adoption. Can you do analytics in Excel? Yes. Ask all users to use the same tools and methods regardless of their needs? Yes. But. The process becomes more onerous, and your goals will likely suffer the consequences.
Long story short? I am a runner. I didn’t come by this skill naturally. And it takes vigilance to not slip back into my old nonrunning ways. In the same vein, your organization may not have been born with analytic DNA. And perhaps, for some, the shift to data-driven decision making may never feel entirely natural. Or analytics will may always be viewed as a necessary evil. Whatever the case, the evidence is clear. In the digital economy, those who exploit their data win. Those who don’t languish or perish.
And regardless of whether your company grew up with strong analytics DNA or not, you can develop the capacity for healthy data-driven decision making. Successful runners and organizations aspiring to analytic excellence alike:
- Clearly articulate their vision. And why it matters.
- Communicate what success looks like by gathering and sharing compelling stories and examples.
- Acknowledge the challenges ahead.
- Identify measurable goals.
- Honestly (and ruthlessly) assess their current fitness.
- Actively engage peers and expert sources to learn what works. And what doesn’t.
- Develop a realistic action plan with frequent interim milestones.
- Publicize the plan.
- Invest the requisite resources and time.
- Acquire enabling solutions as needed.
- Tolerate short detours.
- Embrace learning opportunities and correct course when needed.
- Celebrate and broadcast every victory – big and small.
Kimberly Nevala is the Director of Business Strategies for SAS Best Practices, responsible for industry education, key client strategies and market analysis in the areas of business intelligence and analytics, data governance and master data management. She has more than 15 years of experience advising clients on the development and implementation of strategic customer and data management programs and managing mission-critical projects.
- Becoming an analytic enterprise requires more than analytic tools. Or Hadoop. Or a data scientist. Anatomy of an Analytic Enterprise reveals what it takes to build real analytics muscle.
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