For organizations in the consumer packaged goods (CPG) industry, Data and analytics offers great opportunities and has the scope to provide huge business leverage. But in reality, not many CPG companies are tapping into their great data pool.
If one considers the industry average, CPG organizations lag behind the industry in key aspects of data utilization. Per an industry report, data-powered decision-making in CPG firms stands at 44% despite great potential. Only a few CPG companies – data leaders as we may call them – are gaining in customer engagement and market share.
This article discusses data challenges and solutions in CPG and not retail, though the two entities are usually clubbed. Retail companies (like Walmart or Target) have vast volumes of consumer data as they sell directly to consumers and typically own the relationship with buyers. On the other hand, CPG companies don’t directly sell to consumers but are dependent on retailers (their customers) and third-party syndicated data providers to know consumer behaviour and category-wise performance.
Challenges in the effective use of data in CPG companies
The main reasons why a majority of CPG firms lag in using data analytics are related to people, process, and technology. These may include shortfalls in strategic alignment or operations or factors such as skills deficiency, trust, or leadership. With the vast volume of data flowing around, trust issues around data privacy have become critical. Building trust with customers requires sound data management.
There is another dimension to this: sometimes within the organization, there is a lack of synergy between departments on how much organization data can be trusted, leading to inconsistent consumer targeting and disparate consumer profile data across organizations. Then, there’s the issue of ROI on data. A McKinsey research says, only 40% CPG companies with digital and analytics investments are achieving returns above the cost of capital, consuming precious time and resources that could be otherwise spent for generating insights.
Further, only 40% of CPG organizations can combine multiple data sources – including structured, semi-structured, and web analytics. This cumulative impact results in a lack of data-powered insights to support decision-making and monitor operational performance. For example, mass personalization cannot be achieved unless multiple data sources are combined to form a connected view of consumer interactions.
The shortage of skills – especially in mid- to junior roles – is another challenge. In most firms, data literacy is mainly limited to subject matter experts. Also, less than half of CPG organizations have a complete picture of their data inventory. This limits their ability to apply analytics-based business intelligence and AI solutions to their data assets. The result is inadequate technology infrastructure to leverage data and a lack of alignment between business and IT teams.
Creating business value with data – the way ahead
It is seen that data leaders in CPG enjoy higher operating margins compared with the industry. This is especially important given the inflationary macroeconomic environment across industries. To shield themselves from this challenge, companies should build a data-powered culture to encourage and empower teams to make data-driven decisions for renewed impact.
Swiss multinational Nestle, for example, has launched Digital Acceleration Team (DAT), an eight-month training program to accelerate the company’s digital transformation. Building cross-functional teams to transform workstreams through data and deploying self-service analytics will help companies bring flexibility and experimentation for smooth digital transformation. Visibility and Velocity helped brands in the past; Analytics and Scenario testing will help in the future. Confectionary behemoth Mars is transforming its global portfolio by experimenting with digital twins to optimize its operational speed and create more compelling consumer experiences.
Faster time to insights by adopting AI and automation while phasing out legacy systems is the way ahead. Beauty products company L’Oréal countered the lack of first-party consumer data through service innovation by launching multiple AR/VR-based tools to help consumers personalize their skin routines. Companies can frequently test and revisit products and services by migrating to cloud-based deployments. For instance, by moving a couple years’ historical data into the cloud, Unilever saw better results in transport routing, thereby reducing its carbon footprint.
Privacy guidelines like the GDPR in Europe and CCPA in the US, as well as in other countries, have tightened data regulations that appear more restrictive for CPG companies. By enabling personal data protection of individuals via stringent regulations, it has helped a process where CPG brands need to increasingly plug into external data ecosystems to enable new business models and collaborate more closely on data sharing.
Data leadership – a roadmap worth traversing
To thrive with data analytics, companies should understand their data pool end to end. Is the data source legitimate? Can they collect and process this consumer data? How can they test the quality of data? And how quickly? Without clarity on these questions, it’s challenging to make data-powered decisions about a range of areas – from inventory to trends in the competitive landscape.
For CPG companies, it’s all about implementing superior data management practices. They must realize that having winning algorithms or models is not the difficult part. What’s more challenging is to use it to catalyse change in how decisions are made throughout the organization. It’s ultimately about mining the data correctly … and striking gold!
