How will the consumer packaged goods market of the future utilise data to add value between all the elements in the supply chain?

A data-driven decade ahead?

How will the consumer packaged goods market of the future utilise data to add value between all the elements in the supply chain?

IN the final of the series of three webinars hosted by business analysts RecommenderX on the use of data in the Fast Moving Consumer Goods (FMCG) market, the panel discussed how the Consumer Packaged Goods (CPG) sector will look in 10 years, with a focus on data and how its use will be improved by FMCG brands and products. Contributors included Devan Hughes, CEO of online grocery shopping platform Buymie; Kevin McCarthy, CEO of RecommenderX; Hash Alsaidi, Head of Business Development with RecommenderX; and Dan Ryan, eCommerce and New Revenue Streams Manager with Unilever.

How well is the supply chain of data working for the CPG sector? Will it change over the next decade?

Devan: “My background is not FMCG; I came from commodities. Data flows very differently in CPG and FMCG than it does in the commodities sector. Data flows fast and freely in commodities, with real time reporting and predictions presented frequently. The supply chain of data in CPG is broken by comparison; it moves too slowly and it is far too ‘siloed’ to be as useful as it should be. This produces an inefficient and costly supply chain. Data moves too slowly and tends to be kept hidden in various silos that stop it from being shared in ways that would make it more valuable.”

John: “We are still seeing tension between CFOs and COOs and the cost of data versus the value of the data. We are spending a lot of time and money collecting and cleaning data, but the way the CPG sector is sharing and using data is keeping the value lower than it should be. Until we start processing data more quickly and sharing it more freely, we will continue to see that tension exist.”

Dan: “We are still very much in the middle of this journey to realising the full value of data in CPG. I recall presenting data to clients 10 years ago in the run-up to Christmas and their response was ‘that’s great, but when are we going on half price?’; now we have come to a place where we’re almost obsessed with having data and knowing it is accurate. But we still haven’t really got to the good stuff, the valuable stuff, where we get and process data quickly enough that we can use it to profitably inform our future decisions and actions. Data is only valuable when you use it to produce value, let it help you make better decisions, and unfortunately in CPG, we are not quite there yet.”

Hash: “I would have to agree with Dan; I recall wrangling data a decade ago and to be honest, when working with CPG brands, I find I am still doing that wrangling far more than I should be. One of the problems with data is that it can answer so many questions; you can always ask other questions and get other answers. There is certainly value in using data to know or understand what happened, but when it is used to predict what will happen next and what you should do next, then the real value is unlocked. The systems for

The Future of Data in FMCG and Retail panel included: Devan Hughes, CEO of online grocery shopping platform Buymie; Kevin McCarthy, CEO of RecommenderX; Hash Alsaidi, Head of Business Development with RecommenderX; and Dan Ryan, eCommerce and New Revenue Streams Manager with Unilever.

Amazon Fresh will target us and an organisation like that could buy Tesco Ireland out of petty cash just for distribution. Amazon is an organisation that treats data very seriously and uses it to maximum effect. ”

collecting and cleaning data in CPG are a lot more advanced and effective than the system for prediction and that it the area where we need to, and will, see the most development over the next 10 years.”

Kevin: “CPG has a great many facets; as the sector experiences more disruption over the next decade, there is a danger that we might see even more data sources. Even now we have so many sources: EPoS, sales, supply chain, shopper data and more. The biggest problem that CPG has with data boils down to speed. The hospitality and commodities sectors are already using real-time data reporting to inform decisions and actions and increase profitability. That is where we need to get to in CPG.”

So how do we stop drowning in data without insights in CPG? When and how will that change?

Dan: “The biggest problem we have at the moment is the fact that the various elements involved all have their own data and their own priority bias. Manufacturers, distributors, retailers have their own systems and agendas. The diverse elements in the sales chain need to come together and aggregate data. If we share data faster and more freely, we will see value like the commodity and hospitality sectors have been able to find in their data.”

Devan: “I would echo that sentiment. A major problem we have today is that there are too many humans involved in the process today, with too many differing opinions. With B2C and D2C models disrupting the sector already, there are a vast number of players in the sector. What data should deliver to the CPG sector is accurate, real time reporting that has not been interpreted and accurate systems to quickly model what that data says we should do. Increasingly, that will lead to what we have done, which is use AI to model and shape predictions that will help us. The process could be accelerated massively in Ireland when you consider that Amazon Fresh will target us and an organisation like that could buy Tesco Ireland out of petty cash just for distribution. Amazon is an organisation that treats data very seriously and uses it to maximum effect.”

Hash: “If you look at the stock market, the majority of the process now is AI, with bots making trade decisions in seconds based on highly accurate information; there is no reason why that is not going to be the future for CPG here. There is no doubt that taking some of the people out of the process and increasing the use of AI will make data far more valuable and useful in the future. Over time, the costs associated will fall as early adopters lead the way. The arrival of an entity like Amazon Fresh would definitely see a transformation that would further accelerate that process. Not only that Amazon functions as a marketplace as well as a vendor, it will draw an incredible amount of information from that market, but it will not drown in it; it will use it all to maximum advantage.”

Can you paint me a quick picture of 10 years from now in CPG with data used properly?

Devan: “Bricks and mortar will still be a core element. But rather than the main focus, it will be another place to draw data sets, integrated seamlessly into an overall data-driven digital strategy. Automatic systems and AI will play a far more important and effective role than they do today.”

Dan: “We may well experience even more complexity and growing pains over the next decade, but that will lead us to a point where we see far more aggregated data, shared freely to add value between all the elements in the supply chain for CPG. That is the way that data will be able to deliver on the associated costs and genuinely add value to the supply chain.”

Hash: “The shopper journey will be extremely good, extremely convenient and highly tailored. On the front end, they will have no idea about the incredibly complex systems ensuring there are no out-of-stock issues and the perfect price for the customer. Consumers will love the experience, while the integrated systems in the supply chain work more closely and quickly together to deliver real time value to the supply chain as well as the customer.”

Kevin: “That type of scenario is a real possibility. If we invest in AI power and analysis to reduce the menial tasks involved in keeping the CPG sector running and to maximise efficiency with predictable models based on accurate data, we will find the real value in the data.”

About RecommenderX

RecommenderX was founded in 2016 with the goal of addressing a recurrent business problem. Companies have large quantities of data and they want their businesses to be data-driven; however, the data is siloed, difficult to obtain, and requires significant manual repetitive effort to cleanse and integrate. And all of this before the data is analysed, visualised and mined for insights. RecommenderX blends experience in machine learning, predictive analytics, data visualisation, recommendation and information retrieval to deliver solutions for its customers. For more information, visit https://recommenderx.com.