Forward-thinking executives and business leaders at every level of the modern organization are hard questions of their analytics teams: “Why aren’t we doing more with analytics?” and “When will we unlock the real value hidden in all this data?” and “How do we get more people involved in solving our biggest problems?”
The promise of analytics has been pitched to the C-suite again and again, but initiatives flounder and fail to produce results. A Gartner survey reveals that 87% of organizations have low BI and analytics maturity, falling into two categories: “Basic,” using spreadsheets and personal data extracts, and “Opportunistic,” where individual business units pursue initiatives, but lack a holistic data-driven organizational culture.
Some organizations have a data science team, but struggle with limited bandwidth, difficult deployment of models, and complex tools that rule out democratization of data.
Why You Need to Harness the Power of Data
Despite these challenges, the promise of analytics hasn’t been oversold. Companies that get it right build sustainable advantages and outpace their competition.
Companies that want to win using analytics must develop a true analytics culture throughout the enterprise — and that culture must be driven from both top-down and bottom-up to succeed. A strong and forward-thinking analytics culture is built on the twin foundations of the C-suite championing and enabling the entire organization with democratized data and on curious individuals asking hard questions, finding the answers in data, and implementing change.
In other words, your crack data science team and IT department are great, but this is a revolution on the scale of YouTube wresting control from network television and putting content creation into the hands of individuals. As the #2 search engine just behind Google, YouTube’s democratization of video has shown just what enabling and empowering everyday people with previously-specialized tools looks like.
Developing an analytics culture across the enterprise is no small undertaking. It requires a great deal of self-awareness from a broad cross-section of business units and individual employees. Your organization must step outside itself and reevaluate how to achieve the mission. This will be challenging, so why bother? Why not leave the analytics to the team of data scientists you’ve already built?
The People Who Understand the Problem Should Be the Ones Solving It
The hardest part of the analytics process is figuring out the right questions to ask. And functional knowledge is required to get at those really meaningful questions.
It’s largely ineffective to expect a small analytics team to understand the pressing issues within each department across the organization.
Instead, rely on the experienced analysts and business stakeholders embedded within departments. These are the people who have deep experience and a nuanced understanding of the true problems and opportunities.
At its best, the analytic process is iterative. When you empower front-line analysts, the process won’t end when they get their first answer. The answer will lead to a new question, and the hunt will continue.
Take Analytics to the Frontline
A traditional analytics support model tends to ignore the reality of how insights are gained on the front lines. If analysts and business users must take every question to the advanced analytics or data science team, they lose the opportunity to quickly iterate and explore.
Case in point
Imagine Laura, the sales analyst who wakes up in the morning with an epiphany. “I wonder if sales were low in Region D last month because of the unusually high temperatures.” Under the traditional model she’ll get to the office, call someone in IT, and ask them to run a report.
“OK, why do you need it?” asks the resource on the other end of the phone.
“Well, I’m just curious,” Laura says.
“Do you have a project code I can charge the request to?” IT asks.
And with that, Laura realizes the door is shut. Of course she doesn’t have a project code, given this is just a little more than a hunch she’s working
through. So what ends up happening?
Laura simply quits asking questions. This surrender is one of the biggest fundamental losses within a company. When your people stop asking questions because they know it’s too difficult to get an answer, you’re on the road to mediocrity. This lost curiosity may never cause a catastrophic failure, but it will leave you increasingly stagnant and flatfooted, unable to innovate, react, and win in your marketplace.
With about half the companies on the current S&P 500 likely to no longer exist in a decade, the race to innovate has never been more urgent.
You Need More Than Just Data Scientists
No matter how talented your data scientists are, there simply aren’t enough of them to support the number of requests that will come from analysts across the business. A recent KPMG study surveying thousands of executives in over 100 countries found that Big Data and analytics skills are in the shortest supply, naming it the number one talent shortage in the world.
There’s an entire set of elementary and intermediate analytic tasks that can be offloaded to the line of business. This frees up the data scientists to work on the difficult things they’ve been hired to do, and it gives your business analysts the power to fish for themselves.
Analytics in Enterprises Today
The benefits of a strong analytics program have been clear for some time now, and this means everyone is thinking about how to best deploy the capability. Executives know at a high level that they need to be getting more value from their data. In response, companies spend millions of dollars on massive data warehouses, data lakes, or other repositories.
They buy the tools and deploy the platforms, but the hoped-for results don’t materialize. Executive sponsorship is in place, the money is committed, and the data analytics team doubles in size. But for a company with thousands of employees, the data analytics team will never be big enough.
The effort is made to push the analytics capability out to those thousands of employees, but no one is using the tools. Why?
The 2019 NewVantage Partners “Big Data and AI Executive Survey” found that 72% of participants report they have yet to forge a data culture. It turns out the biggest challenge to building an enterprise analytics competency is cultural.
Why You Need a Culture of Analytics
Even though the tools are in place, employees don’t change their behavior to incorporate new processes or capabilities. They choose to stay in spreadsheets. Teams choose to stay isolated within their functional groups instead of sharing data and analysis across the organization. The reasons for this are as dull as they are predictable. People continue to use spreadsheets because it’s the tool they know.
They don’t have to take time off and learn a new process or a new application. It’s much easier to proceed with business as usual. For an established company, changing things on the fly can be very tricky. However, the benefits of establishing a competency that allows for a culture of analytics are significant.
Consider these top three business benefits of a culture of analytics:
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More people are empowered to solve bigger problems: A culture of analytics democratizes data, spreading access from a small group of analysts to departmental leaders and staff. Data democratization results in more brainpower solving your company’s challenges, big and small. In turn, bottlenecks and silos start to evaporate as individuals access and share data from around the organization.
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Investment in people and tools reaps exponential rewards: In a culture of analytics, the business value of data is apparent, so stakeholders empower the right people and provide proper tools. Technology is not seen as a cost center, but rather an investment with incredible returns.
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Everyone wins with democratized data: You get a trophy. You get a trophy. And you get a trophy! In a culture of analytics, everyone can focus on their specialty. IT still provides governance but doesn’t need to clear every data project. This decreases ad-hoc requests, even if some data democratization does need initial IT approval and support. Analysts get the data they need, and business stakeholders reap the benefits of better insights.
In “The Untapped Power of Self-Service Data Analytics,” the Harvard Business Review explores the challenges to realizing analytics potential. Essentially, they boil down to technology, process, and culture.
The modern analytics era offers the promise of sustained high performance for the enterprise that can effectively harness its data. The platforms and methodologies are easier to use and more accessible than ever before, so the time for tool-based excuses has passed.
Leaders that help deploy the right cultural and mindset shifts can expect to achieve astounding results as they empower everyone in the organization to push together and solve the company’s biggest challenges.
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