The story of struggle in every company is the same – the things we do for efficiency have a way of getting in the way of effectiveness. At its simplest level – this is the reason the wise ones say transformation is a journey and not a destination.
The rant that follows is the result of two phone calls I had early in the morning with old friends 🙂 .
Anyone who has spent even a month of their career inside a company would hear something like “the problem is that we operate in silos”. This was true when I joined the workforce in the 90s and it’s true today. So why do we have silos even though every CEO, every vendor and every thought leader have argued against silos all these years? It’s simply because we need silos for competency building and boundaries are arbitrary. It would be amazing if every marketer also understood company financials in great detail and can make wise choices in marketing spend – but the day only has so many hours and if you want to be great at marketing, you need to spend more time doing it and that reduces time available to learn the nuances of finance. That’s the reality. Silos will be here tomorrow as well – because they are a necessary evil. What is achievable is in building great interfaces between the silos – be it trusted relationships between people across silos, simpler processes and sensible use of technology.
It’s the same case with corporate hierarchies. No one including me likes hierarchies – and want it to be flattened. We are all well aware of the advantages of flat organisations. And yet – we also have to live with the hard reality that to keep ourselves organised and efficient, hierarchy is a necessary evil. What we can do – and rarely get right – is via empowering employees, having great communications, building trust and so on. Jensen Huang has something like 50 direct reports in Nvidia – which I am sure helps keep them flatter than most companies. But none of the CEOs I know in person seem to be able to adopt that – so I am not sure if that strategy will become mainstream.
AI “might” kill silos and hierarchy levels a lot more than any of the past approaches – but that has its own pros and cons.
In any case – one of the known challenges with having a hierarchy in a large scale org is that the people on top of the pyramid don’t always share the views of the people lower down. Optimism about AI is one such topic – what I hear from the very senior execs and what I hear from the less senior ones rarely match.
When it comes to AI – the most common approach is a top down mandate on adoption. For example – I know plenty of CIOs who have rolled out AI based tooling for their large engineering teams. They have PMO teams to track metrics on adoption. Most of the time those dashboards are all green. I talk to the engineers all the time as well – and they have a thousand concerns about embracing AI including the fear of losing their job to an AI agent in the future. The engineers and the middle managers find ways to keep the big bosses happy – either by doing some minimal work with AI to show they are using the tool, or showing higher velocity by being smart about how story points are handled. I used IT as an example – it’s not any different in other functions. Everyone declares success – but the enterprise level ROI needle doesn’t move very much.
On the other hand, I also know tens of cases where AI has given great ROI. Not all – but majority of those cases have some commonality. They were done in employee centric ways – listening to the ground reality, addressing concerns, not forcefully mandating upfront and willing to change course based on learning. The challenge though is about scaling. These cases tend to have modest ROI in real dollars so far even though percentages look impressive. The world we live in is an impatient one and unfortunately also the one that refuses to learn lessons from the past.
When I entered the workforce – ERP was in the hot seat like Agentic AI is today. Almost word for word – the hype was similar about its transformative ability. The reality though is that it took a long time to show the kind of ROI that it promised. The technology was evolving fast and assumptions were changing all the time and consequently estimates were hardly solid. What were initially thought of as best practices had to be changed many times over. If we choose to not be breathless with excitement – we can pause and think through how we got through those times in 90s and how we accelerated fast after that.
I was an SAP consultant. I remember the first projects used to have workshops with COO and GM level folks and ignored the input (including big warnings) of the people manning shipping and packing and so on. After spending 20 hour days fixing problems for months after go live, the whole approach to implementations changed.
Change is quite hard and it takes both time and money. If you look back at failed ERP projects in the past – ( also today for that matter) – they largely failed because the team under estimated the resistance to change. Change management budgets were usually the first to be cut in those programs. The money saved by underinvestment in change management then got spent in addressing the delays – usually by some order of magnitude increase in spend.
Just as we see with AI today – there were plenty of thoughtful ERP projects early on that delivered ROI but they were small and hence no one was impressed. Our industry is used to under estimating the long term and over estimating the short term.
The good thing is that we have plenty of history to teach us how to do this well this time around. If we take the human beings involved along – listen, learn, debate and iterate fast – the acceleration in value will happen and the needle will move naturally in the right direction. This needs the senior folks to constantly ask themselves the uncomfortable question whether they might be operating in an echo chamber.
The AI tech – and its ecosystem – is evolving fast. Even with known issues like hallucinations and potential for misuse – we know enough now to make impactful solutions happen for solving big problems while mitigating the known risks. Let’s do this thoughtfully and set realistic expectations and maybe even have some fun going through this journey!
And Vijay Says... 