Despite Massive Investments In AI And Digital Transformation, Survey Finds Poor Results
The term “digital transformation” has come to mean steps that move an organization towards adopting data-driven business models, typically involving artificial intelligence (AI), big data and predictive analytics technology.
The survey also found that budgets dedicated to this transformation at medium to large-sized companies increased from an average of $11 million to $13.5 million this year.
However, it also highlighted the finding that most organizations still report a gap between their investment in this technology and the impact it is having on key performance indicators such as profits, revenues and customer satisfaction.
In an effort to understand this, it identifies 7 “pivots” – capabilities that, when developed, contribute towards a business successfully bringing about positive growth through a technology initiative.
It found that “higher maturity” organizations – those who had progressed their digital transformation to the point where they are driving positive growth – deploy an average of 40 initiatives targeting these pivots capabilities, suggesting they are indeed a contributing factor.
Deloitte’s chief digital officer and head of innovation, Ragu Gurumurthy, explained to me that three of these pivots stood out as “foundational,” and solving challenges around them often opens the pathways to digital transformation at medium and large-sized organizations.
He told me “The first things companies should do is focus on data mastery and infrastructure, as well as their talent.
In terms of infrastructure, companies need to create flexible and secure systems that are able to balance security and privacy with the need to flex capacity as business demand changes.
Data mastery is about aggregating, activating and monetizing data that is still often siloed and underutilized in order to generate better products, services and business operations that will drive business success.
“Those are the enabling pivots that allow us to begin thinking about transformation.”
Data mastery involves generating value from data to increase the efficiency and effectiveness of business processes.
“People say that data is the new oil in the digital economy, and yes, it is – but in the hydrocarbon era you didn’t need to own oil wells to become wealthy,” says Gurumurthy.
“You don’t need to own all of the data – you just need to know what to do with the data you do own.”
What he means by this is while companies like Google and Facebook may have become giants of the digital age by monetizing the “data crumbs” left by users as they use their platforms and services, not all businesses will need to take this route.
“I would say that 90% of the corporate world is not going to capture value through naked monetization of their data assets the way Google or Amazon does. For the most part, they will capture data to increase the efficiency and effectiveness of their company.”
That could mean finding better ways of targeting customers and understanding their behavior and optimizing marketing and retail channels based on the data they collect. In other words, the majority of companies approaching levels of digital maturity where their data becomes a valuable asset is doing so by creating growth for existing, core products and services, rather than creating new ones from their “data exhaust.”
“It’s about creating a secure environment, where you can launch applications fast and remove the friction in your operations, and think about how you interact with your customers – this is made possible by investing in and understanding your data infrastructure.”
The next key pivot – talent – revolves around the way data is used to understand and nurture a business’s most vital asset – it’s employees.
“This is actually the hardest thing to do,” explains Gurumurthy. “One can figure out cloud migration strategies, one can figure out how to collect and store data, and how to run analytics on it, but its harder to manage change around talent.
