“Never before in history has innovation offered promise of so much to so many in so short a time.” -Bill Gates
In the last decade, we – as data scientists, marketing analysts and overall analytics thought leaders – have witnessed something groundbreaking happen. The digital revolution gripped our very occupations as we knew them, and forced us to change the way we collect, clean, standardize, store, and ultimately, analyze and visualize data.
While this digital revolution brought about necessary adaptation on a lot of different levels, one of the positive byproducts of it included a monumental amount of innovation.
This innovation was caused by an emerging need to draw timely, meaningful and actionable value out of the vast amount of now available, collectable data. Part of this innovation included a shift in strategic focus from one which included instinctual and “time-tested” decision making to one which included more dynamic decision making based on increasingly advanced analytics solutions.
We ultimately found that during the digital revolution, there was a parallel analytics revolution occurring as well. This analytics revolution would bring about massive change, but also necessitate massive levels of innovation. If utilized wisely, this innovation could lead to invaluable efficiency and efficacy improvements across many different industries.
As data practitioners, we accepted the demand for these changes – some more willingly than others – and started adjusting to the new, complex analytics landscape. We found a great deal of learning, both theoretical and experiential, was necessary to meet the rising need.
But, more importantly, we found that if we invested the necessary resources, there was an immense amount of opportunity to leverage one of the most valuable drivers of company and industrial wide growth: innovation itself. This opportunity has never been so prominent as it has been in the last several years.
There is an ever-growing list of the numerous ways you can innovate with analytics to create and capture value (and I welcome you to share your own). Please find below 5 of my all-time favorite best practices to achieve this:
1) Utilize analytics to uncover new, non-obvious relationships in your data. Being able to harness analytics procedures similar to NORA (Non-Obvious Relationship Awareness) can be extremely valuable for any company that is dedicated to advanced insight search and discovery. Discovering previously unknown, strong relationships amongst specific variables and the KPI’s that drive growth in your organization can lead to new avenues for innovation for occur.
2) Extend your analytics footprint to process optimization. It is entirely possible to utilize analytics for much more than analytics-specific projects. While this may seem apparent to some, you would be surprised by how many large, public companies do not track the performance of, and subsequently do not attempt to optimize their own internal processes. Here, the most dangerous theme you can operate on is “we have always done it that way.” Always remember that if there is a potential opportunity for your organization to become either more efficient or effective (ideally both) internally, there is also an opportunity for greater profit capturing.
3) Develop your analytics systems with an emphasis on future growth and adaptability. When investing valuable resources into building the analytics foundation of your organization, be sure to architect it in such a way that it is scalable to any potential future needs. This allows you to maximize how much you can create and capture value. The two most widely employed ways to achieve innovation here are through additional data storage and greater processing power. These, along with an optimal level of automation, will increase the rate at which valuable, down-stream deliverables can be produced. This greatly increases potential insight generation. It is important to note here to also develop your internal processes with scalability in terms of both growth and complexity as well.
4) Balance analytics solutions with creative problem solving techniques. Implementing a mixture of creative problem solving techniques to support the full range of potential analytics solutions can be both a) a powerful way to come up with new ways to answer complex questions and b) increase the accuracy of current or potential analytics solutions by testing them against a wider range of test solutions. Essentially, the more you can innovate to gain a greater perspective on an analytics opportunity, the greater your probability of accurately applying a solution to it will be.
5) Empower your organization with ongoing analytics learning opportunities. One of the greatest ways to support a wider range of innovation with analytics is to spread the good word about its capabilities to not just your analytics team, but to your entire organization. This may include team debriefs, presentations, blogs or other speaking/networking opportunities. Foster a culture of collaboration within analytics; sharing key learnings, insights, best practices and solutions. Learn to be as accepting in these situations as possible, as to support continual analytics innovation across the entire organization.
These are just some of the best practices for using innovation with analytics to create and capture value. Like analytics itself, innovation is a living, breathing process that is ever changing and growing. So – naturally — one of the final best practices I can share with you is to be strategic in your analytics planning, emphasizing flexibility in adapting for future growth.
If you are interested in hearing more about how we can help your organization innovate with analytics, reach out to us today!