With consumer and market insights more valuable than ever, the CPG analytics landscape has evolved significantly since 2020. The Smart Cube’s leading experts in the US and Europe discuss some of the key trends.
In times of crisis, analytics can provide organisations with vital insights and direction. So unsurprisingly, over the last couple of years, they’ve rapidly shot to the top of many CPG companies’ agendas.
To get a complete picture of how the CPG analytics landscape has shifted on both sides of the Atlantic, we brought together two of The Smart Cube’s leading analytics minds from the US and Europe – Nitin Aggarwal and Anurag Kapoor – for a joint Q&A session.
Here’s what they had to share.
Anurag, Nitin, thanks for joining us. It’s been two long years of disruption for CPG companies around the world. How have you seen the CPG analytics landscape shift as a result?
Nitin: First and foremost, the COVID pandemic – and the other major disruptive events that followed – have forced CPG companies to largely throw out everything they thought they knew about their market, customers, and suppliers. The post-pandemic world is a whole new paradigm, and CPG companies have had to utilise analytics to start to chart this unknown landscape.
Anurag: That’s absolutely true. Across Europe, CPG companies have been working hard to establish that understanding quickly – driving many to scale their CPG analytics efforts up, or supplement them with new data and capabilities. Once the game changed and nobody knew what to expect, and teams turned to analytics to provide them with much-needed direction and strategic insight. Very quickly, CPG analytics went from being a powerful supporting tool to a critical capability for thousands of businesses.
With CPG organisations tackling the combined pressures of rising price inflation, supply disruption, and rapidly-shifting competitive landscapes, one of the areas that we know a lot of companies are prioritising today is Revenue Growth Management. How can CPG analytics support successful revenue growth strategies?
Anurag: CPG companies have been applying analytics to help drive revenue growth and devise informed growth strategies for many years. But most of their efforts have been applied at the local level. For example, teams across different geographies are generally responsible for creating their own tooling and models, to solve local revenue growth challenges.
Today however, the challenges being faced by CPG companies are increasingly global. Teams need to create analytical models and tools that, once developed, can be applied across other regions to help solve similar challenges at scale. In doing so, CPG companies can work towards creating consistent, global analytical insights that help them respond quickly and effectively to international risks and opportunities.
That global visibility really represents the next stage of evolution for CPG revenue growth strategies – but there are reasons why that level of visibility and global insight don’t already exist for many enterprises.
Nitin: Inconsistent data availability, diverse data quality, local data regulations, and even complex organisational structures can all make it hard to apply and scale models across geographies. Crucially, those global CPG analytics efforts need to be driven by a centralised team responsible for building and applying them around the world.
That shift towards centralised operations, away from the decentralised approach to analytics used by many organisations today, is a challenge of its own. But the most mature organisations have overcome it and laid the foundation for global CPG analytics success by building analytics Centres of Excellence (CoEs) responsible for model creation, and finding the right opportunities to apply those models internationally.
What emerging analytics use cases are leading CPG companies adopting to help them tackle today’s biggest macro challenges across the globe?
Nitin: With costs rising and supply chain pressures persisting, assortment planning is one of the key areas that CPG organisations are using analytics to tackle. Teams are looking for balanced ways to transfer increases in price to customers, without losing market share and remaining profitable.
They’re applying analytics to increase the efficiency of product assortments and ranges, identify SKUs that may need to be retired, and build product assortments that are better aligned with the challenges, demands, and economic conditions seen today.
Anurag: Another emerging area of focus that’s closely related to assortment planning is around sourcing. Again, because of ongoing supply pressures and rising costs, leading CPG teams are applying analytics to help them understand the complexity of their SKUs – the variety and number of ingredients required to make them, and how exposed those categories are to risk, complexity, and volatility.
Identifying and understanding that complexity is the first step towards reducing it, and ultimately cutting the cost of goods sold. It’s enabling organisations to devise far more precise changes to SKUs than simply cutting pack sizes – the kinds of changes that are far less likely to negatively impact revenue in the process of cost reduction.
Crucially, they’re also using analytics to model the impacts of those changes on consumer demand. Instead of making changes then waiting to measure the impact, they’re using data to forecast the impact that proposed SKU and assortment changes will have on demand at a granular level. That’s helping them make strong and highly competitive assortment and sourcing decisions.
What changes do CPG analytics organisations need to make in order to capitalise on those opportunities and start driving greater value from CPG analytics?
Anurag: One of the clearest areas of opportunity lies in the data sets that CPG companies are using to power their analytics. As they start to tackle challenges like the inconsistency of data across geographies, they need to make use of all data types available to them.
CPG analytics should combine first-party data gathered from the company’s direct operations, second party data from partners such as retailers and suppliers, and third-party data sets that add vital market and consumer insights.
Nitin: There’s also something to be said about the ways that CPG companies think about analytics solutions and capabilities. To deliver the most value, their capabilities need to be able to scale – but that scale shouldn’t come at the cost of local flexibility. They need to adopt mature product or solution mindsets, developing capabilities in the same ways that they would develop customer-facing products and services.
Across much of our work, that’s something that our clients consistently say they appreciate about working with The Smart Cube. We have a lot of experience building globally-scalable and locally-valuable analytics solutions, and we help our clients evolve the way they think about their analytics products.
Anurag: There’s also some work needed to ensure that all the right teams can communicate, share data, and collaborate on analytics that deliver value across functions. For example, when I was talking about optimising SKU complexity, that requires close collaboration between assortment, range, and Procurement teams.
Part of that challenge lies in how organisations are structured. The bigger they are, the harder it is to enable that alignment. Fortunately, that’s something that centralised analytics CoEs really excel at. They can be the bridge that brings functions together to achieve mutually beneficially data-driven benefits.
Nitin: Finally, as teams tackle these new challenges, they can’t afford to take their attention off ongoing changes and initiatives. Efforts to improve data quality should be continuous, as should efforts to evangelise analytics outputs and drive adoption. As we adapt to the challenges of today, we can’t let their scale distract us from the fundamentals of CPG analytics success.
To learn more about how The Smart Cube is helping CPG companies around the world stay on top of category, market, consumer, and analytics technology shifts, and harness data to successfully navigate highly challenging conditions, visit here..