Peter Drucker once said: "Culture eats strategy for breakfast." As I reflect on my 20 years of experience in data analytics, I've found this statement to be absolutely true. My single biggest learning during all this time is that the most important predictor of a company’s success is its data-driven culture.
That’s why at Schneider Electric, we have made it our mission to cultivate and sustain a data-driven culture. By removing barriers and empowering all users to engage in analytics, you create an environment that rewards a data-driven mindset.
Sure, every leader wants a data-driven culture, but the pathway isn’t always as straightforward as it sounds. Before you know it, a once seemingly simple task is so cluttered in nuance, you don’t know up from down.
By sharing my experience at Schneider Electric, I hope to provide some guidance for your journey. I invite you to leverage these tactics in your own organization. Together, we’ll do our part to make data-driven insights the norm rather than the exception.
Table of contents:
A data-driven culture is an organizational environment where decisions at all levels are guided and informed by data. It embodies behaviors, attitudes, and practices that ensure data is readily available, trusted, and consistently used by all to drive outcomes.
However, I believe that becoming a data-driven organization—and the strategies that drive it—varies by company. When it comes to thinking about how I define data culture at Schneider Electric, I return to our foundation: We are a people company with an ecosystem of over 150,000 colleagues, aiming to create an impact by empowering all to make the most of our energy and resources, bridging progress, and sustainability. Both of these sentences—creating an impact and making the most of resources—are fundamentally underpinned by data.
For us, a data-driven culture means data is so infused in our everyday workflows that everyone is empowered to ask questions, challenge ideas, and use data—not just intuition—to make decisions. Fostering this culture helps us unlock new levels of efficiency, innovate constantly, and scale decision-making—fueling a competitive edge across 100 countries over the last 180 years.
As the voice of data in the Customer Satisfaction and Quality (CS&Q) function at Scheider Electric, it’s my job to bring data to life in ways that improve the lives of our team and members. Here are four key components I follow to do that (and how you can, too):
1. Defining clear goals and priorities
In our mission to become a data-centric organization, we aimed for an organization-wide impact. I knew that in order to do that, I’d need to strike the right balance between being technology-enabled and human-centric. To do this, we needed to truly understand our current position and define our goals
That led our team to start with an organization-wide data audit, reviewing how each department and key stakeholders were leveraging data and noting the unique challenges they faced. Based on the assessment, we outlined our desired outcomes and priorities—this became our roadmap.
Ultimately, we wanted a self-service analytics solution that allows us to create a single source of truth to support fast internal communication and swift decision-making. Adopting such a solution would enhance data accessibility, making the entire process of data exploration intuitive and engaging for our users. After an exhaustive search, we chose ThoughtSpot as a catalyst for change and innovation.
💡 Insider Tip: In addition to outlining your goals, priorities, and technology stack, identify key stakeholders across business functions to lead analytics initiatives, manage data accessibility, and facilitate cross-functional collaboration.
2. Getting executive buy-in
Any organization that makes significant strides in fostering a data-driven environment almost always shares one common trait: a committed and engaged leadership team. When top leaders actively endorse. prioritize, and reward data-driven decision-making, it signals to the entire organization that data is a critical asset.
Consider the last company-wide meeting you attended. Did your leadership keep users engaged with interactive charts and up-to-date visualizations that show the trajectory of your business? When your teams see the executive team leveraging data to create engaging data stories to demonstrate their findings they would say, “Of course, they’re going to expect me to do the same.”
In addition, executive buy-in ensures that the necessary resources are allocated to develop the infrastructure and capabilities needed for a data-driven approach. And when workers who embody this data-driven mindset are promoted to leadership positions, they foster that same appreciation for data in their direct reports.
💡Insider tip: One of the best ways to get executive buy-in is to demonstrate the tangible benefits of data-driven decision-making through compelling use cases and real-world examples within the organization. Don’t index the number; instead, share what that KPI means in the context of the business.
3. Focusing on change management
Without a plan focused on people as well as process change, your analytics goals are bound to fall flat. Most users don’t get excited about learning a new analytics tool, even one with natural language search and cutting-edge GenAI features like ThoughtSpot. That’s because they already have a way of doing things—they don’t have time to learn something new unless they see the value in it for them.
If the benefits aren’t spelled out, users will tune out of training, log out of the BI tool, and never log back in. That doesn’t just hurt the individual user; low adoption also hinders your momentum. That’s why you need to approach every use case rollout with the same enthusiasm and opportunity as the first.
Recognizing the limitations of traditional training methods, me and my team developed bite-sized, targeted learning modules called ‘learning pills’ to address specific user needs and functionalities within ThoughtSpot. We diligently mapped out the ThoughtSpot user journey and identified key functionalities that users needed to master to leverage the platform effectively.
With personalized, on-demand training addressed to specific user needs, we saw a staggering 500% increase in ThoughtSpot adoption rate from 2021 to 2023. Even better, users reported feeling more confident and empowered to explore the platform and core differentiators of ThoughtSpot such as natural language search and SpotIQ.
💡Insider tip: Keep gathering user feedback and identifying important use cases. Create documentation, including visualizations and workbooks, that are practical and beneficial for all users.
4. Adopting the right data analytics solutions
In my experience, one key factor that sets Schneider Electric apart from competitors is our ability to pivot whenever necessary. That’s because we provide every worker with a modern analytics solution that delivers insights—not a clunky dashboard siloed within a separate BI tool. With ThoughtSpot, anyone at Schneider Electric in the CS&Q division—quality manager or customer experience executives—can explore data without jumping through any hoops.
Notably, the quality management team witnessed a 75% reduction in overdue derogations. As a result, the industrial automation team saw a dramatic decrease in technical customer issues, from 60 to just 8 year-to-date. Additionally, users in the manufacturing quality department reported significant time savings, amounting to approximately 60,000 FTE hours annually. This transformative shift has yielded strong energy savings and nurtured a culture of dynamic decision-making within the organization.
To me, data culture is more of a journey than a destination. It is an essential element, without which today's businesses won't be able to survive over the next 25 years. The strategies and tactics above are firmly ingrained in Schneider Electric’s DNA, but that doesn’t mean we are complacent. We are always keen on pushing the boundaries and finding new use cases that enable users to extract even greater value from their data.
So what's next for us? We see so much potential and possibility in GenAI and machine learning—and we know that in the coming years, it will help us predict accurate business outcomes, anticipate market changes, and accelerate decision-making for all our energy and sustainability programs. We’re also committed to investing in data literacy programs across the organization, empowering every user to interact with their data and create a greater impact.
Care to see yourself in Vidyadhar Joshi’s position? Sign up for a ThoughtSpot demo and see how AI-Powered Analytics can help foster a data-driven culture in your organization.
