I read with great interest an article in this weekends US print edition of the Economist. The article was titled Why companies struggle with recalcitrant IT. In a nutshell the article explored how software is developed to meet specific needs; specifically:
- Converting business requirements into code is hard work
- Coding will always add varying degrees of error – its just a matter of scale
- Software solutions can age very quickly and become overhead and less useful over time as competing offerings emerge or needs evolve
- Maintenance of that software becomes more costly over time as developers age or decline in number; methods and practices are improved; and even the language used may be superseded with others
In Gartner-speak the article spans many areas of our research but from where I sit this hits home with business applications, application development, and data and analytics. These areas are reliant on software and all struggle with the items notes in the article.
But what are your choices as a leader who invests in software? Firstly, you cannot avoid these issues. Software today may well be the platform on which increasingly more organizational competency and business competitiveness rely. Knowledge, IP and ideas are coded and express an intent for how an organization will respond to customers, or processes and decisions are modeled to secure access to facilities, or process checks for unemployment claims. Software is everywhere and it’s not going away.
Second, the natural response is to do better. Surely, we can step up quality assurance to reduce the bugs; maybe we can insist on interoperability to ensure longevity in how code can operate with new iterations; perhaps we can develop higher level of conceptual models to mask the boring details and neuter their implied future redundancy. All these have been tried, and you will have a budget item somewhere in your IT plan for some of these, I am sure.
But what if there is a third option? Seems to me that we should at least try to reduce the impact of the said challenges. Let’s assume we had $100 bucks a year buget. Should all $100 go to fixing these issues? What if we took $30 bucks and used it to run a different organization that ignores the challenges and that continues to rush, head-in, toward the next shiny thing? Implied in the success of today’s software deployment or project are the seeds of tomorrow’s maintenance nightmare and IT debt. Why not save off a little of your money and deliberately look for the next disruptive software trick? In effect, why not assume failure will come along and eat you up anyway, and give some of your funds to look for the next success?
Sounds logical, right? But it’s hard to do. Can you really stop asking your customers for what they want more of, and instead ask your prospects? Can you afford to press ahead less with currently winning software solutions to help secure the future? Will your current successful investment model, spewing profits, permit a loss-leading innovators dilemma? Can you afford to slow your investment in the current race, just as your competitors go all-out to get to the current finish line?
Of course, it depends. Can you do just enough to play today while laying the track for the next race? Where should you dis-invest now, to free up hard-won funds for tomorrow? ERP? Analytics and BI platforms? Data management tools? Data Warehousing? A little data governance? These are delicious problems to have. They keep us busy. And ignoring the fun these are really important questions. They tie in the idea of innovation, growth and productivity. They talk explicitly about the idea of how you sequence your organizations investments. They refer to the idea of portfolio planning. These are complex or even wicked problems to unravel.
This is the area of research we have stated to dig deeper in 2020 and we hope to do more in 2021.
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