How to launch a modern analytics strategy

We’ve established that we’re living in the defining decade of data. Data underpins the seismic technology shifts of the past few years, transforming the way we buy, work, make business decisions, even value our companies.  

As ThoughtSpot’s co-founder Ajeet Singh said, “Once in a generation, the opportunities to create a legacy increase massively. It happens when truly tectonic shifts happen in the ecosystem. We’re living through one of those times.”

Assuming that you’re ready for your business to join the ranks of those dominating the data era, you might be wondering where to begin. You know that it’s going to take more than just buying some best-of-breed tech and hoping for the best. To truly turn insight into action, you need to secure buy-in for your vision, create new habits in working with data, and drive cultural change.

Here’s how to roll out a modern analytics strategy that will result in true transformation. 

Define your first modern analytics use case

As with any major digital transformation, you’ll begin by identifying use cases for overhauling your approach to analytics. Consider your company’s biggest data pain points: 

  • Is your BI team snowed under with user requests? 

  • Are your data analysts spending all their time on menial data cleaning tasks? 

  • Do you have a major blind spot when it comes to lead or customer behavior? 

From there, create a list of use cases—here’s a handy guide on use case best practices. Next, analyze your list and prioritize your use cases

Start with your top-priority use case—one which will result in significant value for many people in the company, but which is also fairly easy to solve. By that we mean: 

  • You have the data available to solve the use case already

  • The data is clean enough to be used immediately

  • The use case is unsolved by existing tech solutions 

This will help you to secure a quick win and gain buy-in for your more comprehensive strategy. 

Phase your modern analytics rollout

To make lasting change, it’s better to start off slow. Once you’ve picked the right use case to start with, group your end users into two categories: power users and the wider organization. 

Phase one: Power users

When you’re thinking of who to consider a “power user”, don’t just consider technical skills. Your power users are the people who will champion your new approach to analytics across the company and provide you with the feedback you need to make the rollout a success. Ideally, choose people who will be outspoken advocates when they see the results they’re getting, and who already know enough about working with data to avoid a steep learning curve. 

Phase two: Wider community

There’s usually no need to make more than two user groups. If your power users are convinced, and you’ve incorporated their feedback, you’re ready to roll out your new strategy to the rest of the team. When it comes time to secure adoption of your modern analytics strategy, there are two key components to keep in mind.

Secure modern analytics adoption

Answer the question: what’s in it for me?

Learning a new tool or process takes time and effort. As a data leader, you’ll likely have to overcome resistance to change.  After all, we’re already pretty busy managing our existing workload. For instance, most employees in large organizations are using ten or more work-related apps, each with their own user interface and techniques. Small wonder then that analytics adoption rates are stalled out at 30%

If you want more than one in three employees to engage with your new data strategy, you need to show them why they should bother. This is the “Aha moment” that’ll create that feeling of “Ooh, how can I do that too?” 

As Cindi Howson, ThoughtSpot’s Chief Data Strategy Officer, recently wrote, “If you want to become data driven, you have to align your initiative to the goals of the organization, but also to the goals of the individual…If data improves a salesperson's commission or a teacher’s ability to help students, then it will be met with enthusiasm.” 

For example: 

  • Ask users to bring their three most pressing business questions to the onboarding meeting, and show them how quickly they can find the answers with your new data analytics pipeline

  • Choose a use case that includes insights that users typically ask for but haven’t previously been able to get hold of (or have to wait weeks for a report) 

Find out if your organization is a data leader or laggard in this webinar

Focus on data literacy, not technical literacy

Don’t lean too heavily on teaching people how to use the new tools in your analytics stack. For starters, if you’ve built a modern data infrastructure with a user-friendly experience layer, most users shouldn’t need to spend long learning the tools. For instance, if you can search for something on Google, you have enough technical knowledge to use search on ThoughtSpot.

Instead, focus on teaching data literacy—giving your team the ability to create, manage, analyze, understand, and communicate data. Essentially, we’re just talking about the language of business—what different data terms mean, how to interpret data visualizations, how data can influence decision-making, and so on. 

As Cindi wrote, “There is a baseline level of fluency everyone needs in order to be able to think critically about data and to recognize when there are both gaps and biases.”    

A good rule of thumb is to spend roughly 50% of the onboarding sessions teaching people about how to use analytics tools, and 50% teaching users what the data means for them. 

Take your modern analytics strategy to the next level

Once you’ve rolled out the analytics strategy to your wider community, it’s time to find out what else your data can do. How can you embed analytics into the bones of your organization? How can you become a truly data-driven company? 

Here are a few ideas: 

Make data a habit 

Take a page out of behavioral economists’ and apply a bit of nudge theory. Instead of mandating the use of the new tools, or forcing users into lengthy training sessions, try nudging them towards making use of data in their daily lives. For instance: 

  • Set up automated emails to share a snapshot of a high-value Liveboard with users every Monday morning 

  • Share examples of quick wins delivered by your new data infrastructure in your regular internal communications

  • Add “using analytics to drive impact” to your recognition and reward program, and publicly acknowledge effective use of the new tools by non-technical users

  • Include “effective use of data” as a category in employee performance reviews 

Make a game out of it

Gamification has a significant impact on employee engagement, motivation, and psychology

Try: 

  • Publish a leaderboard for most active users of your data infrastructure (such as most searches, most time in the analytics tool of choice, most days using your analytics tools in the past month). By the way, ThoughtSpot has a leaderboard built in. 

  • Run weekly competitions; for instance, who can find the most accurate answer to a business question, or who can find the answer most quickly

  • Set up internal “hackathon” style contexts to solve real-world business challenges with a panel of judges to pick the winner

  • Have a “win of the week”, where users share their stories of using data insights effectively for a chance to win a prize 

Make data part of the conversation

In data-driven companies, data becomes part of how you talk about work, every day. Don’t let analytics remain something for the data experts. Instead, empower every front-line worker with the information they need to do their jobs. 

  • Advocate for data in the weekly stand-ups, in the board meetings, and in the management presentations. 

  • Showcase data wins and return on investment in your internal communications and newsletters. 

  • Require employees to back up their proposals with data, not hunches. Embed analytics tools into your internal apps. 

  • Share Liveboards via Slack. Make data the language that your business speaks.

Time to launch your new analytics strategy

We hope these ideas have left you feeling inspired. If you’re ready to turn these ideas into actions so you can start building a more data-driven organization, then it’s time to start your free trial with ThoughtSpot. And if you’re already a ThoughtSpot customer, you can learn how to create a data-driven culture with self-service analytics in our complete guide.


Adam Ciperski leads ThoughtSpot's worldwide Customer Success team where he looks after the success and adoption of ThoughtSpot. Before ThoughtSpot, he established Customer Success teams at Teradata and Qlik. Highlights of his 20+ years in enterprise software sales include developing the Customer Advocate program at Cognos and the Solution Advisors customer success program at IBM.

Adam lives in Miami with his wife, Carla, and their two children, Theo and Sofia. When Adam is not supporting his children at musicals, plays or swim meets, he is swimming, biking, or running in preparation for his next triathlon.