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"Big data" and predictive analytics demystified

Robert S. Holston
"Big data" and predictive analytics demystified Robert S. Holston

The tornado of press, media, and commentary in the last year around "big data" as the cure all for what is ailing today's enterprises -- from stagnant top-line growth to flat bottom-line productivity --  has been fascinating, confusing, and complex. I keep waiting for the clouds (no pun intended) to open up and a house to fall.

While "big data" is an important enabler, it is robust analytics combined with a CPG manufacturer's (or retailer's) organizational ability to apply insights across product development, store layouts, media and consumer engagement, trade and promotion, and related functions that will drive the sales and market share uplift that will in turn drive profits.

Big data and predictive analytics demystified

Don't take my word for it, SymphonyIRI recently completed research of 160 senior executives representing CPG and retail companies in the U.S. and Europe as part of its new Analytics2020 initiative. Those companies with "above average" analytics capabilities enjoy operating income 14 percent higher than those with less developed analytics practices.

Focus on "good" instead of "great"

Today's hyperventilation about "big data" is reminiscent of past trends when managements convinced themselves that the latest and most expensive enterprise information management systems would cause revenues, profits, and margins to grow, ROI to soar, and the stock price to skyrocket. I was reminded of this a month ago when a client made plans to hold off modifying their price and trade strategy because "big things" were happening in the next 18 months --integrators were on the cusp of completing phase 1 deployment of a new "big-data" system. Waiting years to address current challenges and opportunities just seems absurd. This is especially true when managers can successfully address many of today's challenges with robust analytics delivered in near-real time that leverage multiple and integrated sources. "Big data" shouldn't be the speed bump that slows down practical and strategic execution and activation -- it should be the lubricant to move analytics-based decisions forward. We must remember the warning by that famous IT expert Voltaire, "the perfect is the enemy of the good."

I believe advanced analytics -- available across the enterprise -- will drive innovation over the next decade, if freed from behind the desk of the market research manager. The combination of advanced technology, predictive analytical models, and the proliferation of consumer and shopper data is enabling decision makers to address and anticipate the changing desires of consumers and shoppers, thereby generating more relevancy, personalization, and engagement. De-averaging the marketplace to uncover new growth opportunities is only possible with advanced analytics in the hands of capable talent with the courage to deviate from the practices of the last several decades. "Big data" will be one enabler, but only in so far as it supports an analytics agenda and an organizational capability to commercialize analytical insights across the value chain -- that is, sales and marketing through to supply chain.

Research revealed

To test our beliefs, SymphonyIRI surveyed 160 U.S. and European analytics, marketing, and commercial professionals and queried them about analytics practices within their companies. SymphonyIRI determined those with more advanced analytics capabilities tended to also have higher operating income percentages and stronger stock performance.

CPG manufacturers and retailers with above average developed analytical capabilities are generating 14 percentage points higher in their operating income performance (latest three years) versus their peers who are less developed. This has also equated to a 12 percentage point higher return on their stock performance over the last five years. While certain causality might not be absolute, the trend is creditable.

Our early analysis focused on areas that are central to brand and sales leaders. Analytics are driving value in four critical areas:

  • Improved innovation development and management

  • Granular pricing and revenue management

  • Optimization of marketing resource activity

  • Targeting and personalization of media and 360 degree shopper engagement

The CPG and retail industries are poised for rapid expansion of analytical capability -- with industry participants saying they will double their company's competitive position by the deployment and enterprise-wide availability of analytics and improved analytical insights in the next three to five years. Predictive modeling, simulation, and optimization requirements are expected to see close to a 25 percent increase in importance to decision making from where they are today to where they plan to be in three to five years. The use of manual, ad-hoc, periodic analytics will drop from 60 percent to 34 percent in favor of "always-on" and automated analytics capability. Clearly, there is a strong link between analytics and data -- but it is the analytics that's in the driver seat, with the data as the fuels that powers the "car."

Implications for brand managers

For brand management this means rapidly assessing the impact from marketing activity and changing media, campaign execution, and overall vehicles mid-campaign. Market mix analytical techniques can take four to six weeks to complete and were designed to offer a historical perspective of performance at the end of a campaign. The future will be more grounded in optimization of performance based on high-quality predictive analytics prior to the start of a project, combined with mid-campaign directional analyses to make corrections during a campaign. These corrections will enhance campaign results and ROI. The next generation of marketing "mix-esque" analytics will enable not just planning built from historical views but media agency and retail partner collaboration, and ultimately dynamic execution. It will be "always-on" and will sense to alert media professionals to change course. It won't be delivered in retrospective PowerPoint decks -- it will be delivered via analytics on mobile technology and busting the dynamic of the relationship between media companies and brand advertisers.

Collaborative Analytics will change the media buying, measurement, and economic models by fueling each side with new insights and contributing to an overall collaborative dialogue on how to power brand performance, spend efficiency, and connect with relevance.

For sales professionals this translates to the ability to develop ideal granular price and trade approaches grounded in both a deep understanding of consumer and shopper response to activity. It means focusing on activating 100 percent of the "right" ACV through improved shopper targeting of price, marketing, and other merchandising activities and moving away from "price guardrails" built at aggregate national or regional levels that are designed to connect to the average and non-existent shopper.

Don't ignore the man behind the curtain. Unlocking "big data" and analytics to define and activate a commercial and marketing agenda are highly dependent on a new talent strategy. While it is easy to romance technology and predictive capabilities, professionals who can commercialize insights in new ways are the ultimate determiner of how much and when value is delivered. They are in high demand and their availability in the market is low.

Our Analytics2020 research indicates that the top two barriers limiting organization adoption of analytics, outside of perceptions on price, are:

  • The organization lacks experience applying analytics output (39 percent of respondents)

  • No clear ownership for company's analytics agenda (36 percent of respondents). Clearly, talent and capability are just as important as technology and models in powering the next decade of performance.

The promise of "big data" and analytics is extremely exciting and will no doubt, when executed properly by exceptional talent, change a company's growth trajectory. The path of becoming an analytically-advantaged company has many phases and starts with an understanding of how a company competes in the market, how it will compete in the future, and how it can best connect and dialogue with consumers and shoppers. A well-executed and phased analytics agenda will ensure success and prevent being lured into complexity over big data in advance of the organization's capability to execute on that capability to power performance.

Robert S. Holston is EVP and division head of Symphony Analytics.

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"3D rendering of blu binary digits" image via Shutterstock.


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