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Are You Measuring The Right KPI To Guide Your Business? Rethinking Your Metrics Is Crucial For Crossing The Digital Faultline

By News Creatives Authors , in Business , at October 5, 2021

Our survey of 9,200 executives from more than 5,000 companies found that more than 70% of companies don’t yet understand KPI frameworks or advanced/predictive analytics.* If you believe as I do that successful transformations begin with analytics, this is an important revelation. 

Not measuring the right things – nor using the right analytical approach – means putting your company in jeopardy of not surviving the dual onslaught of digitalization and ongoing global uncertainty.

Our research clearly shows that successfully transformational companies are using data to learn more about themselves, their industries, and the predictable future for both.

Digitalized enterprises are becoming predictive

As companies invest in a strong foundation of data and analytics, they go through three stages of maturity:

  1. The first is an ability to report across the ecosystem: Companies must understand what happened yesterday, and why.
  2.  The next level of maturity is business intelligence, or the ability to know what’s happening today.
  3. And finally, they gain the ability to predict what is likely to happen tomorrow and further into the future.

To complete the three stages above, companies must replace assumptions with data analysis, which is Rule #3 in the “Ten Rules of Leadership” outlined in my book.

To do this, you must use key performance indicators (KPIs)—metrics that tell you how key elements of a product, service, business model, process, application, or audience are behaving. Lagging KPIs tell you what has already happened. Leading KPIs indicate what will most likely happen.

Digital KPIs are imperative to always know where you are, to visualize where you need to be, and to work backward on a plan to get there.

The new key performance indicators – digital KPI

As mentioned above, Trianz’ Global Transformation Study (TGTS) data found that more than 70% of companies don’t yet understand KPI frameworks or advanced/predictive analytics. But the most successful companies or “digital champions” that we found in the TGTS data focused on business outcomes measured in terms of brand-new leading and lagging indicators.

We call these ‘digital KPI,’ but bear in mind that none of the successful companies we studied began their transformation process by focusing only on technology.

Key to developing your future-proof vision and strategy is developing and deploying a digital KPI framework for your organization along the following lines:

Benchmark your organization’s digital maturity against that of your peers, and not just within your industry.

This benchmarking tells you where you stand, where your competitors are, and what the best-in-class and industry averages are worldwide. 

You may be surprised by some of the results. But the data will give you an accurate look at the trajectory of your peers and industry champions, offering new perspectives to fold into your digital vision.

It is imperative that benchmarking (in some form) be started as early as possible, because it may take time to get results.

Develop a long-term vision but stay focused on the next iteration.

You can either develop a long-term blueprint that you arrive at via iterations (accepting that your eventual destination may be quite different than what you envision now), or begin the first few iterations and develop a long-term plan afterward. Regardless, clearly identify the areas that will be digitalized. 

Define leading and lagging digital KPIs.

For each area being digitalized, define a leading and lagging KPI or metric that is specific to your company and business. Often, these won’t exist in the industry and will have to be invented. So, develop your own metrics—it can be a lot of fun! 

Partner with IT to deploy an analytics platform.

Work with IT to identify data sources and automate data collection as well as the delivery of insights through rich, real-time visualization platforms. If you have an existing platform, see if it can be extended. If not, deploy a new one. This will be one of the best investments you will ever make as a leader. 

Determine the frequency for measurement and/or review of the data.

Now that you know what to measure and understand the data required to do so, make decisions about how often to take each measurement and/or when to conduct reviews.

Generate insights and measure progress from digitalization and business impact.

These will be specific to your role, business or function, and industry.

The COVID effect on data analytics and measurement

As part executing the above steps, you will need to consider the effects that COVID-19 has had and is having on your data.

In the time since the COVID-19 pandemic erupted, data being generated across industries has shown very erratic patterns. Certain essential goods and services saw a steep spike in demand. At the same time, demand for other products and services has collapsed. These transactions between various stakeholders and systems are themselves creators, senders, and recipients of data, so the volume of data being generated has also been seriously affected.

The key takeaway: If you’re in a category that is experiencing strong growth, your ecosystem is producing massive volumes of data. If you’re in a category that is experiencing a steep drop in demand, then there would be a corresponding decline in data. These trends are short term, unless the secondary effects from the pandemic on supply chains and the global economy persist.

In either eventuality, it is critical to utilize this window to scale your data and analytics capabilities.

Looking to the future

There is no one singular Faultline for everyone—and there aren’t any “one-size-fits-all” bridges to cross it.

However, by replacing assumptions with data analysis and course-correcting as you iterate, you will take monumental steps toward crossing your Digital Faultline and leaving it well behind you.

*Trianz’ Global Transformation Study (TGTS) data

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