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Retail and Consumer Goods Analytics Study 2018: Overview

4/1/2018
Analytics Study cover

Challenged at one end by digital behemoths and at the other by nimble, born-in-the-cloud startups, retailers and consumer goods companies are under tremendous pressure to deliver exceptional, personalized customer experiences that drive revenue and repeat business.

The emergence of an analytics arms race has forced companies to find ways to expend their limited resources on technologies and applications they believe will deliver the most bang for the buck. 

As retail and CG executives seek to build their analytics infrastructure, governance and talent pools, they must also rethink internal processes and shift their cultures toward an analytics mindset. And even as they gain capabilities, new market demands emerge that continually raise the bar ever higher. 

But the analytics marketplace is also evolving rapidly, offering new capabilities such as artificial intelligence and machine learning, supported by cloud architecture, that carry the potential to turbocharge analytics programs. These not only discern data patterns more quickly, but sometimes even generate their own algorithms to further fine-tune output.

That makes them an ideal match for high-volume, rapid functions such as personalization and replenishment. Signs indicate both retailers and CGs are enthusiastically exploring these next-gen solutions. The race is now on to leverage these new tools to best advantage. 

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Figure 1

Facing Down Big Challenges
Retailers and CG companies are well aware of the accelerating tech landscape and the gap that continually widens between their current capabilities and what is possible. That’s likely why “limited analytics toolset” is consistently a top challenge for both (Figure 1). But retailers are really feeling the pain this year, with 63% citing this as a top challenge, up from 47% in 2017. The inability to integrate data from multiple sources is a related issue, making tools integration a potential choke point in the analytics infrastructure. 

With limited capabilities comes uncertainty about strategy: It’s the top pain point for CG companies (at 39%) that’s also shared by 41% of retailers. Both sides lack the right staff to lead their analytics strategy, and CGs also cite the absence of a single owner for the effort. It’s difficult to stake new ground in analytics without the tools, resources or governance required to execute. 

Executive leadership is struggling in part because they’re approaching the issue the wrong way, says Andrew Walter of AJW-Advisory, a former vice president of IT & shared services at Procter & Gamble. “Too many are not starting from the business problem down vs. the technology/ data up.” Strategy is essential to ensure that investments will support business goals. 

Organizing for Analytics 
More evidence of their shared challenges comes in how companies organize around analytics. Industry analysts often point to a Center of Excellence as the ideal, and many retailers (47%) and CGs (55%) agree. However, just 7% of retailers and 18% of CGs have actually established CoEs. Instead, CGs are most likely to be managing analytics by department, while retailers most commonly make it the responsibility of IT (Figure 2). 

It’s important to remember that analytics is, at its core, a technology, says Greg Buzek, founder and president of IHL Group. “There still is a requirement of systems management, uptime and security. While the budget might come from marketing or operations, it is best if IT is involved. When they are not, security holes are created and that is bad news for any [company].” 

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Sizing Up the Staff 
Although they share similar staffing challenges, retailers and CG companies are addressing their needs with very different resources. Despite the similar size of responding companies, retailers maintain on average 10 internal analytics resources, compared with 28 at CGs. This may reflect the tenure of their analytics experience: CG companies have been at this longer, while retailers started more recently and now may be choosing automation over building internal staff. 

“Within CG, over time, access to information was developed and optimized in separate silos by function, often with different systems and different data standards,” explains Vittorio Cretella, executive advisor with VCAdvisory and former chief information officer of Mars, Inc. Until those systems are overhauled, CGs will continue to need more personnel to manually “connect the dots” and drive insights. 

Despite the staffing disparity, both retailers and CG companies perceive a deficit in their analytics talent and tools. To address this, about one-third on each side are looking to outsource some work to vendors. Similar numbers are recorded for “hiring internal personnel” and for simply “haven’t made any move at all.” At this point, only a handful see artificial intelligence/machine learning tools as a replacement for these resources, although that may change as their use of these technologies matures. 

Figure 3

Achieving Data Alignment 
Another goal for both retailers and CG companies is a “single source of the truth” across the organization. Nearly half of retailers (42%) and one-third of CG companies (32%) feel they “still have a long way to go” toward a single shared data source. But impressively, 23% of retailers and 16% of CGs believe they’ve achieved this goal. 

The journey to a single data source “will last as long as it takes for CG companies to embrace a more data-centric culture, renew their ways of doing business and adapt to the digital economy,” says Cretella. “The sharp contrast between their attention to product manufacturing quality vs. the poor quality of data is indicative of that cultural gap. It starts from the top, with CG leaders needing to make decisions based on data insights and not only on experience.” To address this gap, both retailers and CGs are embracing cloud infrastructure and big data analytics (Figure 3). 

Centralizing applications in the cloud facilitates speed of deployment, faster software updates, lower costs for software, hardware and maintenance, and a real-time, single version of the truth, says Ken Morris, principal at BRP Consulting. “A cloud approach to storing and analyzing product and customer data is essential to achieve access to one version of the truth in real-time.” 

Figure 4

Customer Analytics Leads the Way 
Another common challenge, the lack of clear strategy, is evident in the top areas of analytics focus reported by both retailers and CG companies. It’s not surprising that consumer insights, including profiling and analysis, ranks at the top for both, due to the widespread belief that the path to success lies in better understanding and serving the customer (Figure 4). However, for retailers, the customer is the consumer, so it’s natural that personalization is the second most popular response, since automation is critical to deal with such a large store of data. Retailers are the customers for CGs, so analytics to understand retail demand is closely rated to promotion effectiveness and demand forecasting — all critical functions for market success. 

Collaboration for Common Benefit 
Accessing a broader range of data streams is a best practice for gaining deeper insights into consumers and the business for both retailers and CG companies. Yet despite years of urging by industry analysts, retailers are still moving very slowly toward sharing more types of data or increasing the frequency of sharing. 

But there is some good news. Significant numbers of retailers have moved away from their “never share” stance in favor of regular or at least ad-hoc sharing. The biggest changes came in sharing of online consumer behavior data, where the ranks of non-sharers dropped from 70% to 50% and the number sharing regularly jumped from 17% to 33% (Figure 5). Elsewhere, those who never share pricing data fell from 51% to 35%, and loyalty/CRM data stingies dropped from 53% to 40%. 

Other reports echo this trend toward increased data sharing. However, in Shopper Marketing magazine’s latest trends report, 59% of consumer goods respondents said that, while retailers are opening up, they’re using data sharing as a revenue stream rather than sharing freely in the spirit of collaboration. 

“The days of retailers ‘piecemealing’ data or sharing it as a carrot or stick for other commercial negotiations will be reserved for tactical leaders playing not to lose vs. the accelerating e-commerce players,” says Walter. “Leading retailers need to elevate data access and analytics to a strategic discussion with their CG partners and create new, sustained business models.” 

Figure 5

The Great Analytics Challenge 
Innovation in advanced analytics promises great things for retail and CG companies overwhelmed by too much data and not enough insights. But while intent is high, many companies still lag in key capabilities and struggle to put together the right resources, governance, organization and cultural commitment to remake themselves into fully analytics-driven businesses. As the leaders accelerate their superior capabilities and extend into new channels and categories, everyone else is under significant pressure to put the pieces in place to understand and serve their own customers like no one else can.

To read the study, click on the links below:

Editor's Note: Hare Today, or Gone Tomorrow
Overview: Analytics Maturity Is a Moving Target
Retailers: Wielding Analytics in the Battle for Customers
Consumer Goods: Sharpening the Analytics Toolset

To download the full study, click on the attachment below.

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