Coming Round the Corner - AI in FMCG Category Management.

Hands up if you’ve been worried that AI is going to take your Category Management job?

Late in 2022, ChatGPT burst onto the scene giving most of us ordinary folk an eye opening view of where we are headed. New acronyms like LLM are now common place and much of the industry is diligently watching and waiting to see what the AI impact will be within the food and drink sector. Manufacturers have an absolutely huge and existing wealth of data across their operations in disparate systems, which of course category teams have access to.

One of the initial and significant things I noticed was a Grocer article where Tesco were looking to use AI for Express store ranging, particularly complex ranging with clusters in convenience, which can be very resource intensive. Complexity can make the analysis process lengthy, the outputs and potential changes vast. AI has the potential to cut down that time, but..... and this is a big but, a human person still has to be happy and confident in those results. They need to question and process if the analysis is feasible? They need to be able to explain, interrogate and communicate any recommended actions to other stakeholders.

Having seen some of the AI information that's out in the ether, I have given a lot of thought through work and processes in category management. I've complied a list of the things AI can’t do and that can only be performed by a human brain:

• Talk to a buyer

• Present plans ideas and actions internally and externally

• Chase down things that need to happen asap

• Present in an engaging and impactful way

• Have a view and vision based on years of experience

• Know the best way to engage different stakeholders

• Make small talk

• Know what's feasible

• Go to a conference and see a strategy first hand

• Network with peers and clients

• Build relationships

• Know when the data is wrong and doesn't look right

• Have a gut feeling whether a trend will stick

• Create a story with a mix of data, facts, insights and anecdotes

• Decide it's best to ditch PowerPoint for a presentation and use boards, magnets and mock ups.

• Cat herd all the right people to be available at the same time to share important insights

• Manage a budget

• Deal with a crisis

• Know what is, and isn't likely, to get sign off

.....and so so much more.

What problem is it solving?

With any new piece of innovation or technology, we need to ask what problem can it solve that will drive manufacturers to buy and use it? One of the biggest challenges we face within category management, is at times there's more data than we could ever analyse and look at. This in turn could mean we are not making the most of our data contracts. If AI can do some of the leg work in this space and identifying more opportunities much quicker, that can only be deemed as a positive. But I would say for any high impact pieces of work such as range reviews, promotional planning, JBPs, forecasting and brand days, you will still want to work though the process yourself but utilise AI to support analysis along the way, rather than do it for you.

A meeting of peers with skills sharing and problem solving

Skills loss or skills shift?

I was speaking to David Boon at Dijuno recently where we discussed at depth of how ways of working could evolve. I had initially thought that we might start to see some long term skill losses if we have AI doing more of the analysis work, but David framed it more as a skills shift. If Category Managers have time freed up from analysis, we can invest more of our time into influencing and delivering bold category plans. Essentially, we'll have more time for creating action which could mean is we end up investing more into capability around story telling, relationship building and category thought leadership.

Working on a computer and screen design.

Dynamic dashboards

How many trackers and dashboards exist that need to be redesigned when the world suddenly shifts? How much time could you spend creating a new view of the market to be able to track something different? I do really love the idea that AI might be able to do this automatically, essentially with dynamic dashboards. Something has shifted outside of the norm and AI lets you know about it. David talked of an exciting new world of the 'intelligent business' - where rather than having users adapt to data tools, the tools adapt to the people, delivering highly personalised, engaging insight, just in the right moment.

What about ROI?

Any new technology takes time and money to build, which makes me question the costs of building complex and sophisticated AI systems that will deliver a return for all businesses? Will this just be something that top tier large manufacturers with deeper pockets will be able to access?

Financial reports showing return on investment

So should we worry about our jobs?

I don't think so. I think we should embrace what AI will be able to deliver for us and consider how capability in the future will need to change. We will still need to understand and be able to explain what the data is and where it has come from. We still need to be able to interrogate and understand data sources but we will spend less time doing the doing. The knowledge of how to make a chart look nice in excel will be less valued for sure.