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How to Succeed with Analytics Democratization

How to successfully implement a company-wide digital initiative to democratize analytics.

Strategy   |   Shane Remer   |   Mar 21, 2022

Analytics democratization strategies have a substantial impact on an organization — when they work.

One study by McKinsey showed that less than 30% of efforts succeeded. Another study by the Everest Group showed that 78% of digital transformation efforts failed.

Either way, not good news.

The reasons for the low performance?

  • A lack of buy-in from senior management
  • Strategies that focused on tech more than people
  • Limited resources and skills

But when data democratization and digital transformation efforts do succeed, the results are incredible. According to McKinsey, companies that made early investments in automation and other areas saw a total return to shareholders (TRS) around 74% more than their peers (47% to 27%).

So, the question isn’t can they work but rather, how do you implement a company-wide digital initiative to democratize analytics and make it successful?

The answer? Start with the people.


Why Your Analytics Democratization Strategy Depends On People

The Harvard Business Review summarizes the problem of democratization in two points:

  1. Unspoken disagreement among top managers about goals
  2. A divide between the digital capabilities supporting the pilot and the capabilities available to support scaling it

There’s no doubt technology plays a crucial role in democratization, but prioritizing it above your people can lead to deeper problems.

When Forbes asked industry experts why digital transformation efforts fail, the experts mentioned some of the following:

  • Employees’ resistance to change
  • Miscommunication of project goals
  • Failure to set expectations and goals for users
  • Not coordinating goals across teams
  • Not having the proper skills

Simply put, while the wrong technology can limit or thwart the analytic ambitions of an aligned team, a team that’s not aligned will never get off the ground even with the right tech.
To get them on the same page, you need a strategy.

Aligning Teams Around A Data Democratization Strategy

One of the reasons analytics democratization and digital transformation fail is because people focus on the wrong outcome.

A McKinsey survey showed 68% of respondents cited “digitizing the organization’s operating model” as the most common objective to digital transformation.

But digitization an operating model isn’t the same as improving it. And it’s not necessarily going to make life easier for your people. That might be why only 7 percent of the same respondents said their efforts were successful but “not sustained”.

To align your teams, start with focused questions. Dig deep into the problems your teams are trying to solve. You might already know the answers to many of these questions, but conducting a survey will provide you with valuable information later down the road.

Questions you can ask include:

  • What do you find frustrating about the current data processes?
  • Where do you spend the most time with data in your work life?
  • What’s an analytical tool or resource would you use if added?
  • If we could solve one data/analytical problem for you, which one would have the greatest impact on you?
  • What would you need and want to jump on board a new data project?

These questions help you do two things: (1) Understand the largest pain points in your organization and (2) give you the data to show the value of solving them.

The Value of Solving High-Impact Problems

To start a grand initiative, you often need to start small. But starting small doesn’t mean foregoing impact. In fact, solving just one time-consuming project can deliver a substantial impact.
By solving one reporting problem, Slalom was able to shrink a five-month operation into a five-minute automated process.

Siemens Energy solved a 30-minute process, which sparked a data democratization strategy that led to 350 more use cases in just 6 months, with another 200 use cases lined up.
Both of those examples solved one problem. One was a time-consuming report, and another was a 30-minute repeatable process. Neither was part of a grand plan to democratize analytics, but both lead to transformational efforts — and results.

Starting small means focusing on one common pain point that affects your organization, then putting together a plan to address it.
Here’s what you can do to identify and solve high-impact projects:

  • Look for time-consuming projects: Saving even 30 minutes per day frees up over 130 hours per year per person. If a team of 10 people all have the same problem you could save over 1,300 hours by transforming one project.
  • Identify outcomes: Start with the outcome you want, such as understanding customer purchasing behavior or increasing what-if analysis accuracy. Include other goals, such as company alignment and executive buy-in. Once you have that, it’ll be easier to know what data you need.
  • Plan for scaling: At this point, you can start looking for a platform that scales with you. Strategize and gather input from other departments, including IT. Does your plan solve a problem and reach a desired outcome? Does it mesh with the organization as a whole?

Use the results of your research to put together a cohesive plan, one that checks off as many boxes as possible. Keep it simple, but plan for growth. Then, get ready to align it with your organizational strategy for analytics democratization.

How to Create a Successful Analytics Democratization Strategy

Once you have gathered your information, make sure you can achieve the desired outcome(s) using the budget you have. At this point, you can start searching for the right technology. Depending on the outcomes you have, this is what the technology should be able to do now and/or as you scale:

  • Solve all desired outcomes: This includes objectives such as being available for everyone to use now and later. Analysts. Data scientists. Business users. IT. Etc.
  • Democratize data: Your solution should solve the problem of data silos, make it easier to find the data that’s needed and share assets, including analytic processes.
  • Scale as needed: If you start this project and succeed, can the technology support you as you grow? What if you need a few years before you scale? What if you need to scale back?

With all of this in mind, you can start to focus on gaining alignment, solving a problem, reaching an outcome, and democratizing your data. The road will be bumpy, but you’ll have the strategy you need to ride it out until you’re ready to expand and soon add to the list of the 30% who succeeded.

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