‘Guessing’ is not a business transformation strategy

By Jacques du Preez, CEO of Intellinexus.

Johannesburg, 08 Jun 2021
Read time 4min 30sec

A lack of measurement is one of the main reasons for business transformation initiatives failing or falling short of expectations.

Most modern organisations – whether in response to the pandemic or simply to unlock a competitive advantage – have embarked on some process of business transformation. Those that haven’t will struggle to keep pace with their more data-driven peers, if they still exist at all.

Decision-makers understand the importance of digital transformation. PwC data indicates that 52% of organisations plan to cut or defer investments due to COVID-19, but only 9% of them will make those cuts to their digital transformation plans.

Technology is only an enabler

However, digital transformation is about more than deploying technology. An effective digital transformation initiative should ultimately lead to a broader business transformation, underpinned by a well-thought-out business strategy. Technology is simply an enabler.

To illustrate, many organisations would have had to close their brick-and-mortar locations during the early stages of lockdown. Suddenly, an online presence and strong digital channels for sales, customer service and engagement were essential. But if their business model wasn’t optimised for digital channels, such efforts would fall flat.

For example, a retailer working on a franchise model with little to no centralised processes would find it impossible to implement a consistent omni-channel customer experience across their various locations, causing disconnects and ultimately undermining the success of their digital transformation efforts.

Similarly, a business that relied entirely on a bums-on-seats workplace model would have had to radically rethink its strategy in the wake of the rapid growth in work-from-home. Simply deploying new technology to enable remote work would have limited success as the business model underpinning it is not optimised to make that piece of technology effective.

If you can measure it, you can manage it

As organisations design and implement their digital transformation strategies, they need to constantly measure whether such efforts are delivering on the broader business strategy. This ensures alignment with the overall business objectives – unlocking new revenue streams, optimising processes, boosting productivity, improving talent acquisition – and helps guide decision-makers over where to change course and where to invest greater time or resources.

Here are some guiding principles for using data to measure business transformation success:

Firstly, determine where you will get the data you need to make informed decisions about the business. If the data isn’t available yet, determine the most suitable data sources, whether internal or external, or a combination.

Ensure the data is accurate and complete. If it’s customer data, is every field complete? If you only have a name, surname and e-mail address, for example, you’ll be far more limited in your interactions with that customer than if you also had their age, gender, location and preferences. And focus on quality – you can’t make good decisions with poor data.

Determine the speed at which you need different types of data insights. Some decisions require real-time data and quick course-corrects. Other data – for example, large data sets that take some time to process – can still be informative and valuable two days later. The rapid pace of the modern business environment requires quick, accurate decisions, so make sure it doesn’t take two months to process data that point to problems that need quick resolutions.

Look at the coverage areas for your data. Are all my processes – sales, logistics, HR, supply chain, procurement, financial – covered, and do I have a holistic view over the total performance of my business? Your decision-making power is limited or enabled by the number of areas of the business your data covers.

In addition, do not underestimate the human side of data. You can have great quality data and still make poor decisions about the business. C-level decision-makers need to ensure they are clear on how they use the data to make decisions, and how to measure such decisions. A decision could have an impact on revenue, or employee productivity, or talent retention, or customer acquisition – can you measure what that impact is in a way that helps guide future decision-making?

Finally, culture is vital. McKinsey found that 70% of digital transformation initiatives fail to reach their stated goals, often due to resistance from employees. There is a saying in project management that ‘projects don’t fail, people do’. Is the business ready – from the top floor to the shop floor – for the radical transparency that data-driven decision-making brings?

Once everyone has an accurate data-led view of the business, it becomes impossible to hide or ‘spin’ poor performance. It makes the business more effective, but can expose a lack of performance in certain roles. One study even found that the most common obstacle to digital transformation is the CEO.

How well organisations manage these aspects will determine how successful they are at measuring their success at building true data-driven decision-making capabilities, ones that can transform the business across all its processes and customer touchpoints.

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