Typical savings from concerted efforts to transform maintenance and reliability will yield up to 20% in cost reductions and easily 10 x that value in revenue gains. Elimination of 30% of your proactive maintenance that can be shown to be counter-productive, and elimination of up to 60% of your spares parts inventories can be achieved. Those are the sort of results that good business cases are built upon, and artificial intelligence can help to identify the gains. But can you actually trust that a computer will deliver it?
2024 is proving to be a bad year for consultants. Larger firms are laying off and smaller firms are struggling to survive. A recent analysis of what’s happened in the big firms reveals a lack of satisfaction on the part of consulting customers with an inability to deliver results. They have a point. I’ve heard questions about whether or not AI is replacing consultants. Can it? Let’s see why there’s a downturn, and then let’s see if AI can be used as a substitute.
Many perceive consulting firms as being responsible for delivering improved business results. Some are, but in many cases they focus on product delivery (implementation of large enterprise software systems) not results. Business results are the purview of the big firms’ strategy groups – which tend to be quite small. In Deloitte, EY, PwC and KPMG, those are smaller sized practice groups staffed with highly experienced consultants. They are intended to leverage business process improvement and software capabilities to drive larger engagements. In McKinsey, BCG and Bain, the focus is more purely on strategy, and not on software. Lately they’ve been delving into process improvement work but their hiring models may need to be adjusted in order to bring in industry expertise instead of just really smart MBAs.
Smaller consulting firms are often missing from the news about the consulting industry. They tend to be very specialized, and they have a strong focus on results. Because they are small, they are perceived to be in a different league to the bigger firms. Financially they are smaller, but their expertise can easily outshine the big firms. Like Conscious Asset, some provide subject matter expertise to the bigger firms, working under their banners.
In our case, that synergy with their marketing capabilities helps to bring in more work while we remain focused on thought leadership.
Will AI replace us? In a word, “no”, but it has its place.
AI is quite capable of answering questions and even performing some analysis on client data. I’ve tested it with (anonymous) client data (from a few years ago) to see what it could produce. It actually did a good job, suggested areas for investigation and some for possible improvements. But the analysis could have been deeper. Once prompted with additional questions it did go deeper, but started to get somewhat repetitive in what it was saying. Never-the-less, it has promise as a useful tool in the hands of someone who knows what to look for.
Had it been available when that data was originally gathered, the up-front analysis portion of the work could have been accelerated. That acceleration would be only slight if there was deep subject matter expertise, but somewhat substantial if it was used by those with less expertise. Had a firm lacking deep subject matter expertise used it, they would gain insights more quickly than they might have otherwise, but their lack of depth would result in missing a few rather subtle but important areas to investigate.
My conclusion is that it can certainly help, but not replace a true subject matter expert. It can find information and use it fairly well. It provides some insight, but not overly deep – at least not yet. I might replace junior consultants with relatively little experience, but it won’t replace the highly experienced experts. It can enhance what the experts can achieve, but not without their input and guidance in the form of prompts. AI still needs their “knowing.” After the analysis is done, there will still be a need to investigate on site and in person, and that is no job for juniors or even for your own in-house “experts.”
We are teaming with a data analytics firm and leveraging their tools to provide some of those initial insights. They can help with identification of very specific anomalies, like which parts should be in stock and which shouldn’t, but they can’t do much about the underlying processes that got you to where you are today. If you want some fantastic insight into what you can improve, to save on maintenance and MRO materials spending, and get back some lost production uptime, then let’s talk. Contact us.
Another area of collaboration is the use of AI in producing draft maintenance job plans. We’ve already got a working model. It produces plans that are honestly quite a bit more rigorous than many planners can do today. Soon it will be ready for beta testing. If you are interested in getting your company involved in that, please let me know. Contact us.
Future areas for development collaboration are already identified and I’ll be writing about those in due course.
