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.

The content of this article is intended to provide a general
guide to the subject matter. Specialist advice should be sought
about your specific circumstances.