3 Keys to Becoming an Analytically Driven Organization
"There's an illusion that you've got to be smart to do analytics. I can tell you that's not true."
This assertion comes from Dun & Bradstreet's very own Chief Analytics Officer, Nipa Basu, while discussing the results of the company's 2016 Enterprise Analytics Study. That's not to say analytics is easy; it's not. But, according to Basu, analytics is a practice that can be mastered with diligence and continued learning. "Being smart doesn't hurt, but much more important than being smart is the right training," explains Basu. "Analytics is an incredibly evolving field. Simply going to school and graduating with a degree in analytics is not enough. Today's most effective analytic leaders are the ones that can regularly learn something new and apply it to the rhythm of the business."
Basu herself has more than 20 years' experience but is constantly learning - even from some of her younger team members. It's this continued knowledge and progression - staying ahead of the latest technological innovations and recognizing how analytics functions within the enterprise - that will put companies on the path to becoming analytically driven. "The one thing I urge any analytics team to do that I try to do myself, is to take advantage of everything that's happening inside and outside the corporate walls so the company's analytics practice is the best it can be," says Basu.
Basu leads daily discussions to understand how analytic insights can impact all areas of the business.
As the results of our recent research study illustrate, organizations still have a long way to go before they can simply claim to be analytically driven versus those that clearly demonstrate they are driven by analytics. So what can these companies do to drive an analytics culture change? I sat down with Basu to get her thoughts on what it takes to succeed with analytics.
Understanding What Analytics Really Means
"I don't think everybody is using the same definition of analytics when they're using the term analytically driven," says Basu. "There are those that may be doing the basics - looking at a few rows of data in an Excel spreadsheet or using visualization tools - and consider themselves analytically driven because they don't realize what's possible beyond those fundamentals. On the other hand, you may have a company that has set the bar very high for what analytics can do and therefore view themselves as not being analytically driven enough. Every company has their own threshold for what analytics can deliver, but I think we all need to reach a general consensus of what analytics can accomplish.
"I believe an analytically driven company is one that's actually making important decisions based on relevant data and smart insights."
For Basu, advanced analytics represents a real differentiator. "We're seeing the adoption and evolution of more advanced analytic models to deliver timely, relevant and accurate insights to enable smarter business decisions. The analytics has to be advanced enough that it can help drive previously unforeseen outcomes before it can be considered a true competitive advantage." Basu has seen a ton of analysis, but not nearly enough decisions being based off that data. "We need to get to a point where analytics is seamlessly incorporated into every aspect of team decision-making; that's the modern meaning of the word."
Breaking Down Silos
That said, one of the biggest challenges uncovered in the research was an organization's ability to share the results of their insights outside of their departments - a huge barrier to becoming analytically driven according to Basu's definition. "I am a bit surprised that it's so siloed," ponders Basu.
"I strongly believe in a centralized analytical organization. When there are so many silos with small teams of analysts operating independently of each other, in most cases they're not employing sophisticated analytics; it's likely they're just engaging in simple business intelligence. There has to be an analytics leader that bridges the disparate departments together so they can take the analytics to that next level.
"One department may be using sophisticated machine learning while another is building judgmental score cards. It doesn't make sense. To change that, there needs to be a centralized analytics organization that touches every department. For example, an analyst that builds marketing models should have to have a dotted line to the marketing leader as well as a straight line to the analytics leader who is also connected to every departmental analytics function. Everyone has to know what the other is doing and how it's impacting business in terms of the quality of the analytics being produced. Somewhere, there needs to be a senior leader looking at all of it."
It's still debatable who that crucial analytics leader is. Basu believes it could be something resembling the emerging Chief Analytics Officer but understands most companies may not be mature enough to support that role. "It's a new title, and most companies don't have that leader yet, but they do have senior analytic leaders. Ultimately, there should be someone where the buck stops. Whatever title you give that person, there's got to be somebody who can identify the analytics that's driving compelling insights from the noise and understands how it can be used to drive revenue across the enterprise."
Looking Outside for Insight
At the end of the day, a company's insights are only as good as the data they have on hand. Often, organizations need to enrich what data they have with third-party data. While a large number of analytic teams acknowledged in our study that they go outside for help with their analytics, the percentage was very little. Basu believes they are missing an opportunity to gain deeper insights into their business.
"Without great data you cannot produce great analytics. I think of data like an orchestra and the analytics is the music that's created by the orchestra. Without the orchestra the music cannot be created. The data helps fill in the right notes to make a beautiful opus."
But there's more to it then just data according to Basu. Analytic teams can also benefit from outside analytics support.
"As for my personal experience, because I work for an analytics company that's working with Fortune 500 companies - each with their own existing teams of analytics - I see the benefits an outside approach brings to the table," says Basu.
"The primary advantage is we're working with several companies within the same industry, so we understand the space from all angles. We're continuously investing in newer analytic methodologies and techniques because we have to keep up our competitive advantage against other analytics companies. When someone is working with us, they're getting that advantage that they may not have the resources and tools to build on their own. Let's face it, it doesn't make sense for a company that's not in that analytics business to invest that much money and energy into doing this themselves. Therefore, coupled with our data and models, we can deliver insights that would not have been previously possible."
Basu believes some companies may be reluctant to work with an outside vendor for fear that their intellectual property could be at risk. "It's simply not true," explains Basu.
"Obviously there is a professional level of trust when you work with any client, but there is no difference then hiring your own data scientist that eventually leaves and joins the competition. You can't stop that. At the end of the day we are developing findings for our individual customers, even when we are working with companies that may see themselves as competitors.
"You know analytics to some extent can be industry-agnostic. You're getting the advantage of what we learned by working not only within the industry, but also outside the industry. We're a global company and we know what's happening in every corner of the world and how analytics can be applied to those situations. Often this can only be achieved by partnering with a third party."
Basu believes these are three critical elements every organization must address before they can become analytically driven.
"It's really important to make the investments in all of these areas. From the right team, to the right leaders, down to utilizing the right support network. Analytics doesn't happen by itself, and it certainly doesn't do any good living in silos. When a profitable decision can be made that was not thought of before, that's when you know you are part of an analytically driven organization."