Introduction
A whopping 80% of data in FMCG never gets analysed or utilised. A report from Deloitte and Forbes showed that vast swathes of data that’s currently being purchased by FMCGs is sitting idle.[1] In a world where almost all analysis was being performed manually by people, this was inevitable. But no more.
Traditionally, insight generation in FMCG consisted of the mining of a couple of data sets. The beating heart has often been Sales Audit data (such as NielsenIQ or IRI) – with companies learning more as they bring Shopper Panel data or internal shipments data alongside.
In recent years, data sources have grown exponentially. We can find more growth opportunities – or spending efficiencies – when we bring in additional sources such as retailer EPOS, brand trackers, media trackers, weather data or social media sentiment. So, the way we capitalise on all this data has changed, right?
Data has exploded, human capacity hasn’t
In short, yes it has, a little. Companies recognised the need to provide more people across their business with relevant, personalised insights. The arrival of data visualisation platforms was heralded as a breakthrough by some – and yet those that implemented dashboards have been grappling with the age-old problem: I can now better understand ‘what’s happening’, but it takes hours of manual analysis to understand ‘why’.
In the current era of ‘Insights Transformation’, leaders are looking again at how they can serve personalised insights, opportunities and threats to their sales, marketing and category teams. Roughly half of research departments within organisations have recently taken on a more strategic role. Yet only a handful have made the step to true strategic leaders of the business. This leap requires a rethink of what the Insights function is all about – moving from ‘builders’ of insight stories to ‘architects’ and finding the most elegant solutions to deliver the building. Because it is simply not feasible to serve teams with this level of insight using today’s manual methods.
What does help look like when it comes to unleashing the potential of people and their data?
The challenge we describe is not new – but it can seem intractable. Habits run deep – where commercial teams bring a never-ending deluge of questions to their insights teams, who are so so busy answering the question of the day that they don’t get chance to think about the design of tomorrow.
Furthermore, as soon as someone mentions ‘data’, the false assumption is that this means a major IT project with dozens of stakeholders and 7 digit spend. Indeed, this can be the worst of all worlds – starting with data and IT solutions rather than people and their very real need for insight-based narratives. A big budget play too early in the day can spell disaster.
Connecting data for the story in hand
Good insight hinges on the ability to use multiple sources to provide a contextual story. The iterative discovery of new information/data and the interconnections is how one holistic narrative is created. Using technology that can use, link, and draw conclusions from, all your data allows one true story to emerge.
Historically, people have seen ‘data integration’ as the first step in an insight transformation journey. This can be a big, costly and slow effort, with limited long-term utility because of the nature of advanced analytics. Rather than hard-wire your data into a fixed, integrated structure, there are now more agile methods that access the right dataset in the right way for the right question. It’s still integration – but now seen as a the ‘how’ of storytelling rather than the precursor to any big moves with data.
Finding previously hidden opportunities for, and threats to, the business
Demonstrating early value is critical to securing larger, longer-term investment in the future of insight. If we can move data integration out from being a blocker, we can get to those all-important proof-points faster. This is where automation also comes into its own.
As creatures of habit, people tend to follow ‘known’ lines of enquiry. Likely only using that 20% of the available data due to constraints of time and method. The result? Not a lot of insight feels ‘new’ – and firms risk being exposed when threats are only spotted when they are expensive to fix.
No wonder the GRIT report in 2020 highlighted a hunger for ‘insights that the requester didn’t originally think of.’ That means exploring multiple relevant angles, without bias. Then deriving meaning from those analyses and choosing what to present to the reader.
People back at the heart of insight
Insight is not about numbers. It is about giving people access to compelling, truthful narratives that move people to change. Insight is all about influence.
Insight at scale is about doing this for every commercial leader in the business – not just the senior leaders, nor the ‘discovery experts’.
Solutions must be incredibly user-friendly and distil this plethora of inputs to simple, pithy stories that highlight opportunities or threats – and provide genuine business guidance. They need to integrate seamlessly into existing work so that they are readily adopted by busy teams.
The best way to find out if a solution can work for your people? A very low cost (or even free) trial to get a glimpse of what influential insight really looks like. Using your data. Served to your people with no pre-requisite data knowledge.
Now we’re talking. No, not just talking – we’re moving.