November 24, 2020
Digital transformation and becoming digitally mature have been the concepts that many companies have strived for the past 5 years. Investing a lot of recourses into the idea of having more efficient and automated business processes by adopting digital technology and replacing legacy solutions with newer versions.Unfortunately digital transformation success stories are few and far between with many left to wonder, what are the key measures of successful digital transformation?
Recent Gartner study revealed that although 87% of senior business leaders say digitalisation is a company priority, only 40% have been able to bring digital initiatives to scale. Meanwhile, the spend on digital transformation efforts is rapidly increasing – from around $1,3 trillion in 2020 to $2,3 trillion in 2023, estimates Statista.
Starting with people, not the systems
The difficulty of digital transformation lies in the fact, that it’s a companywide change management initiative. Therefore, there’s no single responsible person or department that implements it. There needs to be buy in from management level and throughout the company.
When we look at good initial indicators for gauging digital transformation success, we can view typical customer support and operations metrics:
· Employee satisfaction
Employee turnover and workforce productivity (revenue per employee) are good starting points to understand both the levels of satisfaction as well as productivity.
· Customer satisfaction
Depending on your type of business, you might be evaluating it based on Net Promoter Score, Issue Resolution Capability, Rate of Returns or Size of Reoccurring Orders. The main thing is that you are able to gauge customer happiness over time and see whether that’s on an uptrend or not.
These metrics on their own say little but when analysed consistently throughout the digital transformation process, they can provide invaluable insight into the mindset of employees and customers – two of the main stakeholders whose lives the digital transformation process sets out to improve.
Process optimisation: better, faster, cheaper
The most popular KPI of sorts for digital transformation is a company’s digital maturity, which is set to let you know, how connected is the company data and how automated are the processes. The trouble with it is that there’s no united formula of measurement. There’s a large offering of surveys and indices to help you compare your companies situation today and in the future, but the lack of standardisation makes it difficult to benchmark against your competition.
Therefore it’s best to focus on KPIs that are easy to understand and quick to follow in decision making. Here are some examples:
· Operational improvement
When stagnant software is changed out or processes automated, it’s important to measure how the change impacts the processes, such as measuring volume or value of production output in comparison to resource input. Good indicators can also be maintenance costs and amount of downtime / uptime.
· Output quality
For physical products there is a variety of measures to evaluate output quality, such as scrap rates or rework rates. These are also different from end customer’s perceived quality and therefore can be a good indication of possible savings thanks to digital transformation efforts. For digital products quality KPIs might be retention rates or reoccurring revenue indicators instead.
· Time savings
Time savings are best evaluated based on individual processes and then compounded to department and overall improvements. This is also the KPI that is estimated to see the biggest improvement through digital transformation implementation.
· Value for money
As mentioned before, the budgets for digital transformation are growing year over year and even the pandemic hasn’t been able to stop it. Therefore, it’s important to see to it that those investments create long-term rewards aka ROI on innovation.
Buckle up for long-term
Digital transformation processes are longterm efforts that don’t have a predetermined finish line, therefore the focus must stay on continued value creation, such as it is in business as usual. The only difference is the larger emphasis on data quality and automation than it has been before.
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