The First Rule of Transformation, Automation, Digitization . . .
I have been in the middle of a “perfect storm” on this topic in the past week.
- Discussions with IT executives about the woeful state of enterprise productivity in the year 2025!
- Business leaders sharing the productivity paradox of expectation, reality and ineffective resolution.
- Exploring the right response to the CEO that announces that “AI will solve our problems, we (you) must move fast!”
- Thoughtful posts from Jack Lampka, Deborah Kops, Glen McCracken (two!), Atul Vashistha, and a couple of early festive wine fuelled ones also . . . 😉
The demand for speed, agility and demonstrable enterprise P&L impact has never been higher.
Businesses have largely delivered cost savings through location choices and wage arbitrage, but leadership regard these as “one and done”.
Enterprise-wide productivity remains a challenge. Check out Solow’s Paradox . . .
“Transformation” is the answer . . . .
But what does it actually mean?
Expectations on AI and Agentic as “enterprise value-creators” are sky-high, and we need transformation strategies and plans that will deliver genuine business impact at speed.
But . . . .
“The First Rule of any technology used in business is that automation applied to an efficient operation will magnify the efficiency. The second is that automation applied to an inefficient operation will magnify the inefficiency”
We continue to make the same mistake with AI that we have made before . . .
70% of everything seems to fail. Digital Transformations, ERP implementations, AI initiatives . . .
Not necessarily the abject failure of “it does not even work!”, but the more insidious failure of disappointment and frustration from the inability to meet the expectations and business case objectives promised in the first flushes of optimism.
Why do we underperform with such alarming regularity and consistency?
- Not because of lack of tech or computing power.
- Maybe a bit to do with our “Blind Spot” for data . . .
- Yes, partly because of silos – executives, stakeholders, business analysts, functional leaders, project managers, software engineers, people that actually do, and take responsibility for, the customer facing work . . . . .
Do we all focus too much on our own silo because it is what we understand best? Is that our comfort zone?
This is just one of the many “Human Factors” that derail our greatest plans.
Classically we have referred to these issues as “Change Management” issues
But is it “Change Management” or “Poor Design”?
Or both?
We know that “Buy-In” is a challenge. Clarity, understanding, belief, support and commitment. “Hearts and minds”.
But the mental model of “Change Management” rankles with many of the supposed “beneficiaries of change” as it implies that we all need “to be managed into the right behaviour”.
But the reality is that the issue starts at the top. Before we even decide we need “change management” for an initiative.
Like you, I am sure, I have observed (and probably caused 😉) a lot of “bright ideas” of transformation that failed because the people that best understand the target process or domain knew very early that the proposed “solution” would miss the mark and would not achieve the desired results. But they just nodded acceptance but, in reality, reinforced their silent resistance.
Last year’s story on the former Nike CEO, hired to “transform” and supercharge company fortunes through a direct-to-consumer (DTC) sales channel is a good example. The new CEO succeeded in his DTC goal but also, unfortunately, also reduced Nike’s market share, delivering a 10% fall in total revenue and losing 20% of its market value – $27bn.
Ouch!
Hubris and overconfidence. He didn’t realise that brand loyalty of consumers to the Foot Locker retail experience was higher than that to Nike itself.
This “hubris and overconfidence” is tied up in our old friend, the Dunning Kruger effect, also . .
“Hearts and Minds” is more than just a change management problem/opportunity.
- Back to first principles: We adopt tools and technologies because they SHOULD speed up tasks, reduce necessary effort and remove friction and irritation for the customer and everyone involved in the supporting activities that deliver for the customer.
Maybe our lofty AI transformation goals are not met for a simpler reason?
We often do not understand how the target domain or process actually works. Maybe it is overconfidence or pride that stops us asking “WHY?”. Think of the retail experience that the former Nike CEO was trying to “transform” . .
How did the retail experience ACTUALLY work? How did customers ACTUALLY perceive the brand and engage in selection and purchase?
Not the way the company or even the Board that hired the new CEO expected, for sure . . .
“Zoom In” AND “Zoom Out”
- “Zoom In” – The truth is “The Devil is in the Detail” when it comes to business outcomes, the processes that drive them, the nuances of the various, desirable routes, and the data that underpins it all.
- “Zoom Out” – We need a “Dual Operating Model” to also consider the big picture, to avoid falling into the “Silos” trap. Whether it is clogged up approvals, failure to meet customer needs, failed IT projects or the “gloopy syrup” of corporate administration, another major cause of business failure is silo thinking. Even the former Nike CEO fell into this trap in the example above . . .
So when you hear another clarion call that we need a “technology overhaul” or a “digital transformation” or “AI to solve our problem”, think twice (I heard this again this morning from a Government advisor suggesting that the answer to the administrative woes of the country was a major technology overhaul).
The first rule tells us that the first objective is to understand the desired outcomes (clearly and unambiguously) and then understand and simplify the operations, the processes, the workflows that deliver those outcomes.
This all takes us back to the Dunning Kruger effect.
Assumptions, avoiding the detail, hubris and jumping to conclusions are all causative factors in this regularly repeated dance.
Discussing AI “strategy” doesn’t crack it.
We have plenty of blue-sky vision.
But we don’t really understand the “Big Picture” of customer outcomes or the “Small Picture” of the detail required for success. We need to better understand;
- The reality of the expectations and behaviour of the customer, colleague or supplier we are meant to be serving.
- The outcomes, the necessary and desired business outcomes and their interrelationships.
- How daily business decisions are made
- The consequences of the policies and controls that WE designed
- The human dynamics, the WIIFM and incentives, both subtle and direct
- How the processes work (really work – not just on a chart!)
- The master data that drives the processes, or is created by customers, colleagues and suppliers.
We need to get better at orchestration. Tasks are just small components. Great business outcomes are created by harmony. The harmony of well orchestrated tasks across functions that deliver the customer experience and the value they are paying for, with their time or their money.
These problems are all surmountable.
But AI does not solve these problems.
It magnifies them.
It makes them worse if we don’t fix them first!
We need exceptional talent and an execution mindset to address these problems. Deborah Kops described the “Talent Gamble” in “Know When to Hold ’Em, Know When to Fold ’Em”.
Once again, it is a “Human Problem” with a “Human Solution” . . .
“The first rule of any technology used in business is that automation applied to an efficient operation will magnify the efficiency. The second is that automation applied to an inefficient operation will magnify the inefficiency”
Jack Lampka issued an exhortation to C-Suite advisors “Stop telling CEOs that AI agents will solve their business problems!”
The companies that succeed in the application of AI (rather than those selling the dream) will not be those spending the most on technology. But those returning to first principles.
There are opportunities and challenges in accelerating digital & AI-enabled transformation for the business at large.
We just need a practical approach to driving successful P&L and Working Capital impact for our businesses, that addresses, at a minimum;
- Business Demands, Expectations and Barriers to Success
- Business Value & “What Does GOOD Look Like”
- Stakeholders and the “Coalition”
- Technologies and the Essence of Digital and AI Success
- The Data Foundations
- Human Factors and the Customer, Colleague Experience (CX)
- The Art of Execution
You can read Jack Lampka’s post “Why do 70% of AI Projects Fail” here . . .
You can read Glen McCracken’s post reviewing the Bain “Guide to AI Transformation” here . . . . and his words this morning on “Silos” here . . .
You can read Atul Vashistha’s post, “Why Does Change Fail” here . . .
Thanks for reading . . .
The First Rule of Transformation
