In today’s fast-moving world, we often miss opportunities to improve processes simply because we’re used to doing things a certain way. By reflecting on existing workflows, documenting what’s happening, and identifying areas for growth, we can unlock efficiencies-even in legacy systems or well-worn routines.
In this post, I’ll share some lessons I’ve learned while optimizing processes, helping teams work smarter, and fostering a culture of curiosity around data. These stories showcase the benefits of questioning assumptions, starting small, and building momentum over time.
Kickstarting a Data-Driven Culture
A true data-driven culture isn’t about blindly following numbers; it’s about being empirically grounded and willing to change based on evidence. But how do you kickstart such a culture? The first step is understanding what you already have: mapping processes, uncovering inefficiencies, and making thoughtful improvements.
Mapping Processes to Spark Better Questions
Many inefficiencies hide in undocumented workflows-processes that run on habit or institutional knowledge without much scrutiny. By documenting these steps, teams gain clarity and can start asking meaningful questions:
- Are there bottlenecks slowing things down?
- Which steps are unnecessary or overly complex?
- Could certain tasks be automated?
Example: In one instance, we mapped a process that relied on “expert knowledge” from someone who had left the company. This exercise preserved critical steps and revealed redundancies that were slowing down progress. As a result, we streamlined the workflow, saving time and making it easier to manage.
Tip: Onboarding new team members is a natural time to map processes. They bring fresh perspectives and question outdated steps, which can help uncover hidden inefficiencies.
Automation: The Power of Simplification
Once processes are mapped, the next step is simplification. Repetitive manual tasks often create unnecessary overhead, but you need to know where inefficiencies lie before addressing them.
In one financial reporting process, I introduced tools like XLOOKUP and modularized Excel workflows to reduce a four-day process to just 30 minutes. The reason this improvement was possible? The team hadn’t yet embraced structured data in tables or learned how to use more advanced Excel functions. By embracing these simple tools we significantly streamlined their workflow.
“Small wins build momentum.”
It’s important to remember that not every inefficiency needs fixing, and to focus on areas where improvements will have the most impact, and that some team members might only care about the outcome-and that’s okay.
While it’s satisfying to optimize a process, having team members adopt processes is what ensures lasting results. What matters is maintaining the overall direction toward better systems.
Creating Reliable Sources of Truth
Another important starting task in building a data culture, is to conduct a data audit. As part of such an audit we consolidated scattered information into a master database. This single source of truth saved hours of searching through emails, reduced errors, and built trust in the data.
Challenges with Legacy Systems:
- Over time, legacy systems accumulate technical debt: mismanaged data, inconsistent naming conventions, and abandoned tools.
- Prioritize systems that consistently show value to ensure long-term success.
Demonstrating the Value of a Data-Driven Culture
A data-driven culture thrives when its benefits are clear to everyone involved. This means showing tangible improvements and empowering teams to innovate.
Simplifying Complex Processes
One example of driving value was simplifying a budget tracker for the projects team. The original tool was cumbersome, with lengthy review cycles that frustrated users. By collaborating with a mentee from the team, I guided the redesign process while encouraging them to take ownership.
The mentee, already familiar with the tracker’s context, implemented the improvements with my support. Once the streamlined tool was ready, the projects team adopted it, reducing review cycles from monthly to weekly. This not only saved time but also encouraged the mentee to explore further optimizations within the team.
“Mentorship creates a culture of curiosity, where small suggestions spark exploration and lead to organic improvements.”
Highlighting Data’s Commercial Impact
Sometimes the value of data-driven processes isn’t immediately obvious but has significant downstream effects. For instance, in one project, we validated vendor data against internal metrics. This helped identify inaccuracies, stabilize financial processes, and reduce potential risks. The value of this project has be evident however difficult to quantify.
In another example, I introduced an AppSheet tool to streamline field operations. This app eliminated double-handling forms, halved error rates, and standardized naming conventions for digital assets. Beyond operational efficiencies, the app boosted team morale - by showcasing individual contributions-by tracking completed forms in real-time.
“Team members saw their contributions reflected in the data-like forms completed or time saved-which made their work more meaningful.”
Sustaining a Data-Driven Culture
Kickstarting a data-driven culture is just the beginning. Sustaining it requires addressing resistance and fostering a mindset of continuous improvement.
Overcoming Resistance with Small Nudges
Change is often met with resistance from personnel that are used to doing things the way they are used to. Small consistent steps can help overcome resistance, by introducing tools gradually, documenting workflows, and demonstrating clear benefits, encourages teams to adopt new practices at their own pace.
“Some team members will come on board, others will step away, but every step forward strengthens the organization’s ability to adapt.”
Think of sustaining a data-driven culture as an ongoing process similar to that of internal audits. The goal is to refine workflows and ask better questions-not to enforce rigid rules but to guide progress in the right direction.
Conclusion: Start Small, Think Big
Driving, demonstrating, and sustaining a data-driven culture doesn’t happen overnight. It starts with small, consistent steps-like mapping workflows or simplifying a process-and grows from there.
The key is to stay curious and keep asking, “How can this be better?” By building on small wins, you can create a culture that values continuous improvement, innovation, and collaboration. And that’s where real transformation begins.
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