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And no, tech debt is not the CIO’s problem…
One of the striking insights from AlixPartners’ Digital Disruption Survey 2024 was the correlation between a company’s projected growth and the strength of its legacy systems.
Of the businesses that felt confident about how well they were managing legacy – either because their legacy systems are relatively new or under control – well over half (59%) were forecasting either slight or significant growth for the coming year, while only a quarter worried about a significant or moderate threat to revenue. By contrast, this figure fell dramatically to just 2% for those who stated their systems represented a major weakness to their business.
Theoretically, therefore, it ought to be straightforward to make a compelling business case to invest in legacy systems and address tech debt. However, in reality it can be difficult because of the perception that doing so will require a complete and costly overhaul of architecture – the rewards for which a company’s current roster of executives may not be around to reap. Many companies, particularly low-margin businesses, are also scarred by previous capex failures, so instead deal with the problem via a seemingly never-ending cycle of quick fixes that, over time, only serve to add layer upon layer of tech debt – and an ever-increasing tax on the cost of future change.
And the consequences of all this from a business and investor perspective? A direct hit on value creation and an erosion of business competitiveness, manifested in a “boiling frog” scenario with slow and steady erosion of EBITDA.
Painful tax on “run”, deadly tax on business transformations
One of the problems is that a lot of companies have a blind spot about how tech debt accrues in the first place.
It doesn’t just build up in run costs – it also comes from the wasted costs associated with the change itself – be it efforts to fuel future growth or build new business models – which can materialise as poor data quality, overly complex integration, or knowledge gaps within the business.
In fact, the “tax” on change can often far exceed the tax on run. At AlixPartners, we’ve identified that wasted costs can account for as much as 30-40% of the costs of change, while the tax on run is typically 10-20%.
A lot of companies don’t fully understand, or cannot quantify, this tax on change and therefore don’t know what to do about it. However, we have seen “change taxes” exceed 40% in some cases, particularly when legacy complexity and manual processes are dominant.
There can sometimes be an acceptance – albeit reluctantly – that project costs will overrun, without a clear understanding of how, where and why. If companies knew how much “tax” they were paying on the cost of change, with it established as a key IT metric expressed as a percentage of an overall IT budget, they might think differently about how they approach the problem. In addition, tracking how much this tax was increasing year on year while root causes remain unaddressed would provide a compelling case for resolution.
The good news is that tools and technologies exist – many of them powered by AI – that can help companies build a better understanding of how, where, and when tech debt is accruing year on year.
At AlixPartners, we’ve worked with companies to help them see a granular breakdown of their tech debt across a number of key metrics. How much of their tech debt is a result of obsolescent technology, for example? How much of it is down to unnecessary complexity – e.g. poor documentation of code, or an inability to reuse/repeat code? How much is down to duplication of systems, e.g. following M&A activity?
Whole-scale transformation, or a pragmatic approach?
In terms of taking action to reduce tech debt, the solution is twofold.
Companies need to be clear on their pain points and look for pragmatic solutions. Of course, there will be circumstances where a whole-scale ERP transformation is required but often, less radical changes – such as making systems more modular and manageable – will deliver what the business needs.
Pragmatic solutions will vary across companies, industries and sectors, but could include approaches like leveraging AI to analyse code (for example, to identify ways to make code more readable, and therefore more modular and reusable) or migrating applications to low-code/no-code.
However, without board level buy-in for investment in new approaches and new technologies, companies are likely to remain wedded to a sticking plaster approach overseen by the CIO.
So, to secure executive support to address tech debt in the first place, there also needs to be a change of mindset in a few critical areas.
This includes acknowledging and accepting that dealing with legacy issues – in essence, risk management – is no longer about partial and periodic changes to systems built to last for a finite period. Dealing with legacy today is about ensuring your systems are adaptable enough to respond to – or capitalise on – disruption, and remain competitive through innovation. For example, in retail, AI can help businesses to understand and predict individual customer needs and behaviour in microscopic detail. But retailers held back by obsolete legacy systems will struggle to harness the opportunities afforded by AI to provide a hyperpersonalised customer experience, which could result in lost custom.
Some companies are already thinking about legacy and disruption together, but many are still yet to address their blind spot around how tech debt accrues in the first place.
With access to granular insights into how tech debt is building up in their business, companies can start to answer the critical question – how much tax are we paying on the cost of change? If that’s a question that you can’t answer – or have yet to ask – then it’s time to put it on your agenda.
