I recently did a video on the Solow Paradox and RPA to explain how RPA overcomes the Solow Paradox, which seems to be making a resurgence. What I didn’t expect was the number of people reaching out with questions about both and wanting to get more insight, so I thought I’d expand my thoughts with an article.

Let me first explain the Solow Paradox. The Solow Paradox was coined after Robert Solow, a Nobel Prize winning economist from MIT, who in 1987 famously said, “the computer age was everywhere except for the productivity statistics.” In today’s vernacular it could be translated as “technology is everywhere and not a gain in sight.” 

His premise was that for all of the technology spending taking place within organizations, the level of productivity wasn’t increasing. In fact, it was going down. The theory seemed to reverse in the ‘90s when the cost of semiconductors declined, and technology became more affordable. This enabled companies to use technology on a larger scale, but beyond that they were finally starting to understand how to harness it correctly and take advantage of the advances.

In 2019, we have once again returned to the ‘80s in the sense that technology spending is through the roof, but productivity and efficiency within companies is once again diminishing. To add insult to injury, a recent Gartner report stated 46 percent of the most focused on IT projects within organizations fail. 

Let’s reemphasize that—46 percent of respondents said that the thing that likely mattered most wasn’t delivering. Combine that statistic with the decline in productivity and you can see that IT in Corporate America is dealing with serious issues.

My position at ATC gives me a front row seat to this as we help companies with their digital transformation journeys. If companies fail to digitalize and transform, they will be left behind. That said, there are so many solutions, SaaS platforms, and approaches that companies are left buried in options, outcomes, and unmet expectations.

I’m sometimes surprised how few companies even know how many different platforms they are running within their organization. I’ve never had a company able to answer that. Once they take a count and we regroup, the number always leads to a surprising outcome. Combine that knowledge gap with the inability to connect and build proper alignment between systems used to gather reports and the effectiveness for company health versus the effectiveness of the platforms and their failure to deliver as promised. You end up with a dilemma that is sometimes easily solved by abandonment rather than fixing and making sense of what is already there.

Technology is clearly transforming how we work, but it takes time for organizations to harness, use, and make the most of it. This is where we currently stand.

When you consider the technological breakthroughs of the past, it took a long time for them to show their effectiveness within companies and within the economy. A part of that comes from not having the right workforce to match up with the new technologies. Additionally, companies need to redesign themselves in order to make the most of new technologies. New generations are on the horizon, so it is critical to meet their expectations. 

Both have a dramatic effect on wages output and our overall U.S. GDP. It’s all tied together, as any decent economist will tell you. Scott Stern from MIT got it right when he said, “If I tell you we are having an innovation explosion check back with me in 50 years and I will show you the impacts —general purpose technologies take a lifetime to reorganize around.”

What is needed?

Companies need to redesign themselves so they can change quickly, adapt to new technologies, and take advantage of tech in a measured way as soon as possible. They need to emphasize a culture that is about learning, unlearning, and relearning in order to be as flexible as possible and overcome the rigid corporate infrastructure and lack of available or non-existent talent. Organizations also need to take advantage of the ways to connect their systems and to get the right mix of enriched, high-quality data that is actionable. 

Seek to really understand your current ecosystem and all of the platforms you are using. Eliminate the ones that are redundant—You’ll be surprised at how many there are. Put efficiency metrics and accountability on platforms and systems to hold them accountable for the forecasted and actual results. I have seen more amazing demos of products that couldn’t deliver their brand promise – cut the contract and move on.

The future is coming, and the future is here. Only those brave enough will have what it takes to differentiate, change, and challenge the status quo.