The KPI Blueprint for Digital Transformation Success

Digital transformation can’t happen with unclear goals or an unclear definition of success.

Nor can it happen if you’re using unclear or outdated metrics to measure progress and calculate returns on DX investments. In other words, clarity is everything.

Companies need clearly-defined metrics to measure progress toward those goals and understand whether actions and investments are moving them in the right direction – or sending them down a destructive path.

In this article, let's understand how to identify the “right” KPIs for measuring DX success. Let's also look at some common examples and when, how, and why you might use them to answer specific questions about your project.

What Makes a “Good” Digital Transformation KPI?

Digital transformation KPIs, like digital transformation itself, are hard to define because they’re so specific to the individual organization and its initiatives.

But, there are some universal qualities “good” KPIs have in common:

• They link directly to a core business objective. Digital transformation always links back to a specific goal — whether that’s improving inefficient processes, capturing market share with innovative new business models, or empowering employees to do more with fewer resources.
• They answer a very specific question about your business. To accurately measure the impact of each action, your best bet is choosing KPIs that answer specific questions in a way that tells you what needs to happen next.
• They’re easily measured and understood by non-technical users. Business leaders and end-users alike should be able to instantly understand where things stand, what it means, and what needs to happen next in order to course correct the game plan or build on past wins.

According to research from MIT Sloan , companies tend to report poor results from DX efforts. Yet, those same companies consistently pick bad or misleading metrics such as how many processes users ran per session.

Much of the problem points back to the fact that companies often have a hard time breaking up with “ legacy KPI perspectives” that undervalue the role of KPIs by using them to track performance after the fact.

Key Performance Indicators to track DX

Again, every organization will track different metrics to determine whether their digital investments are delivering the returns they were hoping for. It’s also worth noting that because transformation is always evolving, your KPIs aren’t set in stone.

The metrics that make sense right now might not align with future goals — so, don’t get too attached.

That said, let's include some “evergreen” KPIs you should be tracking regardless of DX goals.

1. Return on Digital Investments

Return on digital investments is one of the most common KPIs for tracking DX initiatives.

These projects are massively expensive and demand a huge amount of effort from everyone in your org. It only follows that business leaders want to make sure that it was all worth it.

The idea here is simple. You’ll want to look at the amount spent on tech, training, hiring, etc. related to your DX initiative, then compare that total to the amount of revenue that was generated in the time since making that transition.

Keep in mind, ROI can seem pretty minimal for the first few stages of your transformation. Initially, you’re trying to figure out whether you’re heading in the right direction. Long-term, you’ll be able to get a better sense of how successful this project was.

2. Revenue Generated from Digital Technology

For many organizations, measuring how technology innovation impacts the bottom line is crucial.

As Capgemini VP of AI Engineering, Goutham Belliappa explains in this 2021 article , revenue from commodity services is no longer as important as revenue generated from innovative new capabilities.

Companies are moving away from cost-containment measures and toward DX investments that allow them to provide more value to customers and increase market share.

While this digital transformation KPI might sound almost identical to ROI, there’s a subtle yet important difference between the two.

ROI focuses on measuring whether DX investments enabled you to achieve a specific objective. That objective might be increasing revenue, but it could be something like streamlining employee onboarding or automating manual processes.

Here, your goal is connecting digital transformation efforts directly to the bottom line. For example, how do new business models translate to actual profit margins? Or, how have DX investments helped you improve customer acquisition, retention, or overall customer experience?

3. End-User Adoption

Digital adoption is another big one — you’ll want to be able to learn how — or whether — employees are engaging with new tech, platforms, or processes.

You can measure adoption rates in a few different ways:

• Overall adoption rate. Percentage of active users compared to the total number of users who have access to a particular tool/platform.
• Retention. Percentage of users who continue using a feature/app/process.
• Daily/monthly active users. Number of users who use app/feature/service in a given day or month.
• Average time per session. Average amount of time users spend engaging with a specific product or feature.

These metrics can give you a sense of whether users are committed to new processes and tools.

They won’t tell you whether or not users are effectively leveraging these new tools. But, they can help you understand things such as whether your change management strategy is working or whether teams are adjusting to new habits or workflows.

If adoption seems low, it could mean that the new solutions are too complicated, a poor fit, or you haven’t provided adequate training. In that case, you’ll want to capture feedback from users and try to identify what went wrong.

If teams are adopting new solutions and actively using them, you’ll want to make sure they’re getting the right results. If they’re not, you’ll need to tweak the process and see if things improve.

4. Employee Productivity

Done right, digital transformation benefits employees in two key ways. First, automating mundane, low-value tasks allows them to spend more time on rewarding work, which in turn, benefits your customers and your company.

Second, eliminating silos makes it easier for employees to collaborate and access the information they need to do their work.

Tracking employee productivity allows you to determine whether investments in automations or collaboration platforms resulted in efficiency gains. You can measure employee productivity in a few different ways:

• Team/individual performance. You’ll want to find out what kind of impact DX investments have had on employee performance. Typically, you’d do this by comparing your baseline to employee performance after implementing the new solution. For example, since implementing better collaboration tools, has your sales team been able to close more deals, larger deals, move deals through the pipeline faster? Or – has automating manufacturing operations improved product quality or efficiency gains?
• Employee experience. How have DX investments improved employee experience? In this case, you might look at how new tools/optimized processes have (or have not) impacted employee satisfaction or burnout. For example, you might measure the percentage of roles that allow employees to work remotely to measure the quality of their experience. If you then discover there’s a link between remote work and employee satisfaction, you might then improve retention by offering more flexibility to workers.
• Impact of process automation. You might also measure the impact of automating manual tasks like submitting timesheets, generating quotes, scheduling, etc. Are you seeing fewer errors? Are customer satisfaction scores going up? Are employees making decisions that produce better outcomes?

5. Data Governance

According to Salesforce , data governance is the “number one” KPI for measuring digital transformation success. As companies ramp up their DX investments, digital footprints get bigger and harder to manage.

Without strong, streamlined data governance processes in place, it becomes much harder to reach critical DX goals. Worse, it can create complex problems.

You can measure data governance success by looking at changes in:

• Adherence to data governance policies. Implementing data governance policies requires orgs to develop and document standards and processes that outline how data should be used, who has access, and so on. To measure compliance with new policies, you might look at how each department follows guidelines, whether access controls are working, etc.
• Data quality scores. You’ll want to measure data generated by key processes and functions against three key dimensions: completeness, accuracy, and timeliness. Continuously tracking these scores enables you to ensure DX investments continue to have a positive impact.
• Number of risk events. Risk events include things like fines, penalties, or poor decisions caused by bad data, misreporting, or client churn. After implementing data governance policies, orgs should see fewer risk events. If there’s no difference or the problem gets worse, you’ll need to dig into the data to determine where the governance function went wrong.

6. Share of Business Processes Enabled by AI/ML

Measuring the percentage of your business using AI and machine learning can help you understand how mature your DX strategy is.

That said, this metric is only a starting point for learning more about business processes for further optimization.

Automating business processes doesn’t mean those processes are delivering the right results. Nor does it make sense to use AI in certain instances.

Your best bet here is to look at how many processes are currently enabled by AI and ML, then either focus on identifying manual processes that can or should be automated or measuring the efficacy of AI-enabled processes.

7. Sustainability

A recent PwC survey found that 59% of CFOs say sustainability and ESG will be integral parts of long-term strategic planning before the end of 2022 (that’s like right now). It only makes sense that sustainability goals are converging with digital transformation. Read the article by the same author on enabling ESG goals through a digital perspective .

Organizations are increasingly leveraging AI, ML, and big data to reach emissions targets and supply chain goals.

For example, the IoT allows businesses to capture and analyze resource data and energy consumption across systems, job sites, and facilities. AI, on the other hand, can make real-time decisions to drive the best possible environmental outcome — using measurements, historical data, and external data sources.

Or, you might collaborate with a network of technology partners to achieve ambitious sustainability targets faster. In any case, business leaders might measure the impact of their DX investments against the following goals:

• Compliance with environmental regulations
• CO2 emissions
• Energy consumption
• Waste reduction
• Share of suppliers that meet environmental standards
• Percentage of product/packing materials made from post-consumer waste

Final Thoughts

The reason digital transformation KPIs exist at all is because they help businesses achieve game-changing results through big digital initiatives and incremental improvements.

While this all might sound simple, it’s harder than you might think.

In some cases, cases, making KPIs are helping, not hurting your efforts might involve significant changes to your culture, org structure, and workflows.