Why forward-looking capabilities are more important than ever for manufacturers.

Companies leaders need to look forward not back.
Company leaders need to look forward not back.

By Venky Rao, managing director, North America lead of Accenture’s Consumer Goods & Services industry group

The majority of manufacturers know their future success lies in becoming fully data-driven and insight-led—connecting internal and external data to create functional insights that can be easily shared and used by decision makers across the business.

Some have made good progress on this journey. Others are still just getting started, burdened with outdated technologies, overly static processes and a workforce that don’t have the necessary skills for the future. But wherever they stand right now, two key developments have brought new urgency to the question for every manufacturing company.

Why rapid insights matter now more than ever

The first is the pivotal nature of this moment for business. The pandemic has thrown so many cards up in the air, and we’re still waiting to see exactly where they’ll land. Consumer habits and behaviors have been shaken up and longstanding business and operating models disrupted.

The path to growth for manufacturing companies has rarely been less clear. However, the ability to use data intelligently to sense and respond to changing market conditions and patterns of consumer behavior has never been more important.

The second key development is the rapid advances in real-time data and analytics technologies, specifically artificial intelligence, and machine learning. It means that, rather than simply analyzing what happened in the past, companies now have the ability to spot new and evolving patterns as they happen.

This is a much more powerful way to approach data-driven decision making. In effect, it allows the business to “learn from the future” by predicting and anticipating change before it happens. And it’s even more crucial given recent disruption. Analytical models based on historical correlations are more likely to fail in periods of high volatility.

The challenge, of course, is making sure all this new intelligence is usable by the business. Accenture’s Business Futures report has found that while over three-quarters (78%) of C-suite executives of consumer goods companies say they’re increasing their real-time data capabilities only (41%) say their people are actually using it in their day-to-day work.

What’s more, the research shows just over a quarter (27%) of organizations are completely confident in their abilities to foresee and respond to future events. So, there’s still a lot of work to be done.

Three reasons to look forward, not back

When a manufacturer acquires these forward-looking analytical capabilities, new things become possible. Take personalization. This relies on having a cloud-based architecture able to collect and process real-time customer data to deliver the right contextualized messaging at the right moment on the right channel. For example, Carlsberg’s cloud transformation has enhanced its ability to generate customer insights and use them to innovate at pace.

Similarly, P&G’s cloud-based Consumer 360 solution consolidates consumer data to effortlessly deliver hyper-personalized experiences at scale.

The ability to respond to demand volatility is another key benefit. Advanced analytics can transform the resilience of digital supply networks where all parts of the value chain are continuously connected. We’ve seen, for example, one North American food company enhancing its ability to balance supply and demand in real time by using data from a range of sources to segment its supply chain.

Then there’s the whole raft of opportunities in promotion optimization, pricing, price pack architecture, and retail negotiation. We’ve worked with one global consumer goods company that’s transforming its sales productivity and its B2B customer experiences by equipping sales reps with data-driven insights on trade partner preferences.

Five things to get right

There are some key steps that leaders of manufacturing companies can take to move its analytics journey into a higher gear:

Lead with business value. As you plan new analytics investments, it’s vital to stay focused on the business outcomes you’re targeting—and to continually measure performance against them as the program progresses.

Focus on critical data. Typically, around 10 to 20% of the data drives 90% of the business value. These critical data elements need to be identified and prioritized for investment.

Ascend to the cloud.  In almost all cases, getting data insights at speed and scale means leveraging the cloud. Data therefore needs to be a central requirement of the enterprise cloud strategy and architecture.

Look beyond pilots. Innovating, experimenting, and testing are all vital parts of being an agile and responsive organization. But, ultimately, data and analytics solutions need to be scaled up for real-world use if they’re to deliver full value.

Think about skills and culture. The company needs to ensure it has the analytics talent and skills both to generate the right insights and also, crucially, to make use of them in practice. CPG’s will need to reskill and source new talent on the one hand, while driving organization-wide cultural change on the other.

Learn from the future—and set up the present for success

Forward-looking predictive capabilities are going to be more and more important as we emerge from the pandemic. It’s essential that manufacturers act now to embed these more advanced forms of data intelligence, build up their data “muscle power”—and capitalize on the huge opportunities on offer.

venky rao accenture
Venky Rao

Venky Rao is the North America lead for Accenture’s Consumer Goods and Services industry group. Venky works with the C-suite of leading companies to set strategy and guide growth, developing offerings and thought leadership to help consumer goods clients become more agile and innovative, transform and reshape their businesses for growth. He specializes in technology enabled business transformation.