I have been fixated on the study for how organizations allocate capital. One of blogs in 2016 teed up some ideas I was working on at the time: Where You Spend Your Firms’ Capital Matters. This was followed up in 2017 with More on How Firms Make Capital Decisions. Most recently there was this: Yet More on Where You Spend Your Firms’ Capital Matters. This might suggest to you that I have a passion. It is also a beautiful thing. I am exploring decision making (data and analytics) and economics both at the same time. It can’t get more delectable than that.
My studies have continued and I just bumped into some new material I just had to share. Here is an important quote from an old book: “…[I]nvestment decisions, as to their magnitude, and even more as to the concrete form they are likely to take, depend at each moment on the prevailing composition of the existing capital stock.” The quote is from Capital and It’s Structure, by Ludwig M. Lachmann, published in 1956. How I alighted on this treasure is due to another book I am reading: Restarting the Future- How to fix the intangible economy, by Jonathan Haskel and Stian Westlake. As with so many books I read, I have to pause and read another that is referenced in the former.
Its Your Choice and What You Do Next
Capital and It’s Structure is a real gem despite its age. Rebuilding after WWII was still happening. The Cold War was building. Central Banks were not that dominant. Winston Churchill was superseded by Anthony Eden as PM in the UK. Dwight D Eisenhower was President of the US. And it seems that around this time new ideas were emerging that explore the theory, structure and composition of capital.
The quote highlights something that has vexed me for several years. Surely what you decide to invest in as a CEO, CFO, or CIO, is impacted by what you previously invested in? If you invest in, say, analytics and BI this year, isn’t the success of that investment impacted by what you invested last year? If last year you invested in a little data management, and some governance capabilities, perhaps your analytics investment that follows would be more impactful? What if you hadn’t so invested and instead invested in ERP? Would that lessen the impact of the analytics investment that followed?
What Does the Data Say?
We have tried to unearth data to help explore this idea. Several years ago we ran a survey and we published some high level findings. See Sequence Your Data and Analytics Investments to Maximize Business Value. I was a little disappointed in the effort. The concept seemed innovative, but we were not able to find enough folks who could talk knowledgably about the range of investments we were looking at. However the findings were at least directional. Yes, there is some data that infers a dependency for some investments. There were examples that suggested investing in foundational practices did lead to higher return on subsequent investments.
A colleague of mine, Jitendra Subranyan, recently revisited the data set and worked out yet another cool question to ask of the data. We just published those findings. See Data and Analytics Benchmark Findings: How CDAOs Can Achieve Cost Recovery on D&A Investments. We effectively took out the sequence angle in the data and instead analyzed each periods’ investment as a discrete investments. This new analysis exposed some intriguing implications for investment returns. But many questions remain as to the impact of each investment over time.
What is Capital and What You Do With It Matters
It seems that some investment behaviors may impact the likelihood of a successful investment, defined as cost recovery. Such behaviors may depend on the degree to which an ROI of some kind is evaluated ahead of the investment. Others may include a firms risk appetite, which might lead to self-enforced success. Additionally smaller and more well defined investments may be more reliable in terms of likelihood of success. But there are different kinds of capital. So the mix, or the structure, makes a big different to success.
All in all it seems that economic theory in this area is strong. The mix of capital should be taken into account when you plan the next D&A investment going forward. The particular mix could well influence the rate or even likelihood of a return or successful investment. Knowledge capital is critical, not just money or software or infrastructure. As Mr. Lachmann notes in his book, you don’t see railways being operated by staff using knowledge “from 125 years ago”. Why would we invest in new technology every year but not always upgrade our staff and their knowledge capital at every step of the way? Or innovate with new business process or decision re-engineering capital? In modern parlance, why would invest in new analytics, data science or AI technologies but also, always, upgrade our data literacy, management, organization and people skills?