Last year, labor productivity in the US dropped at the fastest rate in 75 years, with five consecutive quarters of year-over-year decline. In recorded data since 1948, that has never before happened. And, while productivity in the final quarter grew faster than expected, the long-term rate remains low. In fact, rates of productivity growth across G7 countries, including the US, in the last 50 years continue on a downward trajectory.
This slowing productivity surprisingly has occurred during a period of growth in technological innovation — that is, the era of digital transformation. On this paradox, McKinsey analysts observed: "Technology has lifted productivity for some sectors and firms, yet its benefits have not been fully captured nor broadly shared. In a recent survey, companies report that digital transformations fail five times more often than they succeed. … A colossal opportunity awaits if the country can collect the benefits of today's technologies (never mind what's to come) and ensure that its dividends are spread economy-wide. … To be ready to capture value from digitization today and the new technologies of tomorrow, firms will need to build their capabilities with the right investments in skilled talent, operating practices, and platforms."
There's a lot to unpack here, but, fundamentally, investments in digital transformation — often an amorphous budget category for enterprises — have not yielded their anticipated productivity and value. Blaming remote work on its face and worker churn doesn't dig deep enough and misses a day-to-day reality businesses and their workers experience. In the wake of the tsunami of money thrown at digital transformation, most businesses don't actually know what technology they've acquired, or the extent of it, and how it's being used, which is directly tied to how people do their jobs. Now, AI transformation represents the biggest change management challenge organizations will face in the next one to two years.
How can we possibly improve productivity in the AI era without knowing what software is under the hood at our businesses and how workers are using it — or not?
Moreover, with the average enterprise using approximately 1,900 business processes, how can we track software use across workflows? The rush to embrace AI software is further complicating these problems, as enterprises have little visibility or control over how these apps are being used.
To move forward, a more measurable digital discovery and integration must replace the behemoth of digital transformation. That means businesses must take a close look under their hoods and do three things to improve productivity and the value of their software investments.
Discover What's There and Dismantle Redundancy
Based on a survey of 1,700 senior business leaders and 2050 employees at organizations with 500 employees or more, across 16 industries, The State of Digital Adoption Report, 2024 found that enterprises vastly underestimate the number of apps running in their tech stack.
While executives at large enterprises believe they only use 21 applications, the actual number is more than 200. That's quite a figure to take in: they only know about 10% of the software that's running on their tech stack. And to complicate things further, 21% of these applications are AI, which executives oftentimes have little visibility or control over. These same large enterprises experience about $16 million in wasted digital transformation investments annually because employees don't use their software correctly.
The first step must be to find out what's there and what's redundant. What applications are duplicating the features and functionality of other applications? Knowing what's there also involves uncovering the use of shadow IT. Anyone with a credit card can purchase software, often well meaning and often on the company's dime through a line item on the budget that's vague and doesn't reveal the acquisition. Lack of visibility into what software is running and what shadow IT exists creates both compliance and cybersecurity issues.
Companies often hire a consultant to deal with this problem. That's an expensive and time consuming approach and they may not be gathering all of the intelligence needed for full visibility. For example, they might rely on basic login data, without understanding session length and other data. They may have a view, but no ability to act on it. They may have tunnel vision around cutting costs and licenses, without adequate context and insight around such cuts — and that's not strategic.
So, an effective solution, like a robust digital adoption platform (DAP), must easily and from a single vantage point provide complete visibility into what software exists in an organization and how it's tied to business processes.
Assess Access and Current Usage
Once a business has a real source of truth into knowing everything it has, the next step is to fully understand access and usage. For each application, can you assess whether it is being used? To what extent?
How is it being used?
How many seats are using it?
What are all of the details on license allocation?
Who are the people using it and what are their roles?
What roles are slated to use it, but not doing so? Why?
Can the seat be switched to someone else?
Who really needs the access to the software?
Who needs to be using it, when, and to what degree?
Every week, enterprise employees spend close to seven hours compensating for poor technology experiences, including access and use issues. These include spending extra time on tasks because they don't know how to use software, they are waiting for support to respond to queries, or they need to ask colleagues or the internet for help. To maximize software ROI, enterprises need to update their change management programs to ensure employees get the support and more intuitive software experience they need in the flow of work.
When access and usage gaps exist, there must be an immediate and easy way to understand and address those — and to end the frustrated underutilization of software vital to business processes.
Optimize Usage and the Full Power of Software
Successful digital adoption that creates value also means employees are able to use the right technology for their role to its full extent and that they're happy doing so. They should have a seamless, enjoyable experience that makes their job easier — and frees them to think creatively, interact with customers and colleagues, and offer the full range of their talents to the business.
This means that assessing and ensuring use isn't enough. That use must be correct and optimized. The question becomes: are employees using all the functionality that can aid their work in the best way possible?
What are their impediments to optimized use and to leveraging the full power of the resources?
Having that level of granular insight into user experience and impediments is crucial.
Employees may use half of the features of their software, or not even that, because of a routine they've settled into that "works well enough." They might be effective to some degree, but they could be more effective and productive if they were able to optimize use without suffering through a tremendous training lift. If you have a Lamborghini at your disposal, but can only drive it in second gear, the power, speed, and potential that's lost can be breathtaking.
An AI-powered DAP goes beyond application analytics to behavioral analytics. It enables understanding of software usage in the context of the workflows that span multiple applications. It measures where users are starting, stopping, and where the friction points are, task by task. It makes more of a business's data actionable with tools that easily deliver personalized help to people in the time and place they need it most. By tracking software adoption progress over time in a clear and measurable way, businesses can chart efficiency KPIs by application workflow and by business process.
More productive and sustainable business growth must emerge as a fundamental feature of the new phase of AI-driven digital transformation we're in — and wasted software investment must become a thing of the past. To better navigate technology change at your business, know what's there, who's using it, and how it is being used for maximum impact.