May 28, 2017
Examples abound: we've all read how Netflix has used viewership data to design and produce new series that are adjusted to viewer behavior and preferences. Waze is also an example of the power of big data and analytics. Companies built solely on data, such as The Climate Corporation, have been successfully acquired.
As easy and seamless as the end result may seem, many companies are still struggling to make data and analytics work for them. The data journey is indeed promising, but companies are still struggling with the fundamentals of data management: reigning data in, getting business units aligned with data solutions and creating data products that are embraced and adopted. The last point is critical because it highlights the importance of leadership and culture in successfully adopting a data and analytics culture. Progress is complicated even further by the noise created in the marketplace by things like big data, machine learning, artificial intelligence and the Internet of Things.
The truth is, a lot of these buzzwords have been hijacked by vendors that portray technology solutions as silver bullets that will solve all problems. They imply that by acquiring these technologies alone, companies can solve all of their challenges and start implementing solutions right away. Similarly, companies believe it's enough to hire data scientists, equip them with technology and just hope for the best.
We are beyond the point of asking why companies should get into data and analytics. Using data is a core competency that is starting to make a difference between organizations that succeed and those that fail. It is imperative for companies to define and start executing their data and analytics strategies as soon as possible.
That said, companies need to focus on a few things that I call the fundamentals of the data and analytics journey.
Let's take a look at each of these points in detail:
In my experience, this is one of the most fundamental elements companies should consider when delivering data and analytics solutions. It's also one of the most overlooked.
"We are beyond the point of asking why companies should get into data and analytics."
In the data and analytics space, the lack of balance between these three elements manifests itself in many ways.
Similarly to the points above, team's leading data and analytics work need to have a laser focus on the business needs of the company and how data solutions can help address them. This requires data teams to be in close sync with the business teams, with focused conversations on understanding what the real business problems are. Many times, the relationship between business and data teams is transactional in nature, putting data teams in an 'order taking' kind of role. Data teams need to elevate themselves out of this position, focusing the relationship on delivering high-value business solutions.
Recently, I was in a session at a data and analytics conference led by Jared Souter, CDO, First Republic Bank. One of the key points he shared was the need for data teams to understand that momentum forward is more important than perfect trajectory. Data teams need to ensure that value is delivered quickly, in an agile way that allows business teams to realize concrete results in the short term.
"Many times, the relationship between business and data teams is transactional in nature, putting data teams in an ‘order taking’ kind of role."
This can and has to be done without losing sight of the long-term vision for data and analytics: short-term gains with a long-term view. Don't wait until your solutions are perfect or let a significant amount of time pass before implementing them. By the time the solution is delivered, the business context may have changed, rendering the solution useless. Delivering small, quick solutions also has the added benefit of allowing business teams to face less change when adopting new solutions.
There is no doubt that there is plenty of value to be realized from leveraging data as a core competency. As business processes become more digital, the amount of data available has increased significantly. Organizations that focus on the right priorities, in the right way, will be able to realize the most desirable benefits.