- Part 1 - Introduction
- Part 2 - Spell out your ambitions
- Part 3 - Select the organizational structure
- Part 4 - Perform a proof-of-concept
- Part 5 - Execute
Step 5: Continue to learn and refine
As with any complex undertaking, one must accept that 100% success is essentially impossible the first time around. Even if you've done every step in a manner you believed to be correct at the time, things will inevitably go wrong, and that's OK. Initial execution should always be followed by a period of reflecting, learning, and refining. Perhaps the business needs are not exactly as planned. Perhaps priorities must change due to customer demands. Perhaps there are technical issues that require resolution. All of these are common situations that arise after the first implementation of a Data and Analytics initiative. The key is to have a flexible platform and open mind. As I stated in previous posts, iterating on an idea and continuous improvement are not an admission of failure nor an assignment of blame. This is exactly what is supposed to happen. Gone are the days of old-school business thinking where a company needed only to focus on doing a small set of things as perfectly as possible for as long as possible. Technology, business, and culture are changing far too rapidly to get yourself all worked up over achieving perfection.
Business now is in a constant state of evolution. There is a quote commonly attributed to Charles Darwin and his research on evolution that is actually just paraphrasing his writings but still captures the essence very well. "It is not the strongest species that survive, nor the most intelligent, but the ones most responsive to change." This concept can be directly applied to modern business. No matter how strong, smart, and high-performing a company is right now, it is the company's ability to change that will make it successful in the long run. Change does not just happen at the top when setting the direction for an entire company. It must be imbued into the culture so that even something as small as iterating on a Data and Analytics project is looked upon as a positive. As long as you have spelled out your ambitions and decided what success looks like, you will get a really good idea what is on-track and what is off-track from the metrics you've designed to monitor your progress. It may even be necessary to change the criteria for success and/or the metrics. Just be sure to proceed collaboratively, honestly, and transparently. Prioritization during this phase is key. Everybody will have an opinion, and there will be so many possible avenues to take that it is very important to approach them in an organized manner to keep things manageable. The methodology for prioritization will change from company to company, but it must always align with the success criteria.
Speaking of change, the tools and techniques in the world of Data and Analytics are changing very rapidly. In my experience, this change is even faster than most other technologies. Although it is not necessary for most companies to stay on the bleeding edge, it can be easy to fall behind your competitors or become stuck with older, incompatible versions of software if you do not stay on top of things. Keep this in mind as you build out your Data and Analytics program. You don't need to latch on to every shiny object, but you do need to stay educated on the latest trends and use your success criteria to decide which will help you get closer to that success state or even adjust your idea of success to set the bar even higher.