2018: Who ate my Digital Investment?
Digital investment does not follow the rules of good, old ‘R&D’ investment.
Digital investment does not follow the rules of good, old ‘R&D’ investment.
As you look back on the year that has gone by, are you left wondering about what happened to all that effort and money that you poured into Digital?
If you are struggling to identify ‘returns’ on your digital investment, you are not alone.
Why are we so befuddled by the elusive nature of returns on digital investment? How is it that while the promise of digital seems clear and convincing, the results are so hard to get? What don’t we ‘get’?
There are two parts to approaching this mystery of Digital Investment. One is about the nature and level of problem you are trying to solve through digital investment. The other is about the thought process that guides digital investment.
This article will focus on the thought process that guides digital investment: How our approach to digital investment is rooted in traditional notions of investment and how that is, indeed the problem.
Our investment instinct, and our financial systems, built on the foundation of ‘capital’ expenditure, influences us to manage digital investments with the same dynamic as we managed good old ‘R&D’. In reality, digital investments do not follow the rules and conventions of good, old ‘R&D.’
Three factors make all the difference.
The people factor
Most of digital investment dollars are spent on people such as coders, solution architects, and business analysts. Most of traditional ‘R&D’ dollars went into plant, machinery, labs and facilities. The price of talent, unlike machinery, varies over the duration of investment. Talent can also walk out of the door. The output of talent, unlike machinery, varies per unit of investment dollar.
As an input, while the same dollar will buy the same piece of physical equipment for you or your competitor, that is not true for every dollar that is spent on talent. Factors such as brand and leadership may lead you to spend more/less money for the same quality of talent.
Above all, we are not wired to look at returns on ‘people cost’ with the same degree of precision as we are with ‘capital’ expenditure. ‘People cost’ start assuming the characteristics of overhead costs rather than investment. Without warning and surreptitiously, these costs start moving up, in line with inflation, or some meaningless metric such as % of revenue.
If a leader says, “I need one more machine to solve the same problem,” they sound foolish. However, a leader can get away with a passionate plea such as, “My team is over-stretched. I need more resources if we want to achieve our digital objectives.”
For all the above reasons, it is critical to tag every dollar of digital investment in people to revenue dollars.
The time factor
We have all read and learned about the ‘indivisibility of capital.’ You buy one piece of equipment, then you buy another. With good, old ‘R&D’ investment you could not ‘stage-gate’ your investments with as much flexibility as you can with digital investment.
Digital investments give you the ability to rent resources, acquire talent on tap, and most importantly, segment your investments in narrower stages - in the shape of milestones. It is also much easier to test the output of digital investments at early stages. Establishing and fine tuning these stages plays a key role in the success of your digital investment.
Expressed in another way, digital investments follow a continuous curve while traditional R&D follows a discrete (step) curve.
The data factor
If data is the raw material, your client is the pilot plant.
Most digital solutions can only be tested on real data. If you are developing a new toothpaste or noise - cancelling headphones, these can be tested in your own lab and a small sample size of consumers would do. However, if you are developing a new digital, risk-based solution for the banking industry, you need real time data that is only available with a potential client bank.
When the client is your research center, the identification of market need must be sharp and well-researched. Unfortunately, most often, people react in an opposite way. They are seduced into developing an MVP that is more minimum than viable. The realization that the first failure, because it is on a client site, is the end of the road, comes too late.
In Conclusion:
If your digital investment practices in 2018 followed the old ‘R&D’ model, success has probably eluded you. It is not a minor consolation that you are not alone.
You still have time to leap ahead.