By Walter McGuigan, partner, Battalia Winston; Joe Carideo, partner, Battalia Winston; and Roy Lowrance, manager director, NYU Center for Data Science
Leaders in the consumer packaged goods and retail industries know that big data analytics can provide valuable intelligence about their consumer base, marketing efforts, pricing structures and R&D initiatives. The possibilities are nearly endless, and a number of industry heavyweights are already reaping the rewards of big data investments: integrating media analytics with consumer insights for more effective ad targeting, mining social media data to identify opportunities for richer customer engagement, and having a deeper overall understanding of how investments in marketing and R&D are (or aren't) driving actual sales.
Consider P&G, who announced earlier this year that they're dedicating 30 percent of their media spend to digital advertising because it enables "effective and tighter targeting of a message to a consumer." It's the combination of analytics behind those ads–bringing together rich data about a consumer's behavior, relationships, purchases, lifestyles and demographics–that allows digital ads to be so targeted. Big data helps brands target specific groups of consumers more directly, offer content specifically tailored for those groups, and ultimately drive engagement and sales.
As CPG and retail leaders begin to fully embrace the importance of investing in big data analytics, they're recruiting leaders–chief data officers, data architects, etc., to pioneer these initiatives in their organizations. But how can executives, who may have limited familiarity with the technology behind big data, be sure that the leaders they hire will set them on the right path? When vetting candidates for this mission-critical position, executives need to ask these five questions:
1. How will you protect the privacy and personal information of our customers, prospects, and employees?
CPG and retail companies should prioritize data security over all else, and must make the right initial investments to avoid the nightmare Target experienced last year. Any big data leader must have a strategic plan from the get-go for protecting privacy and minimizing fallout in the event of a breach. Additionally, all companies endeavoring into big data must clearly communicate to their customers how their data is being collected and protected. Failing to properly inform customers can turn into a PR nightmare, but it can also lead to customers attempting to opt-out or intentionally obfuscate their data.
Because data security is so imperative to the success of any big data initiative, it's no surprise that many chief data officers are coming from the financial services sector. In fact, someone who has led an affinity program at a major credit card company may be the ideal candidate for this type of role because they would not only understand what data is available and how it can be collected, but also understand how to protect the data and what's required for proper compliance.
2. How can we leverage our channel partners to learn more about our customers?
Big data is so attractive because it can potentially address an industry-wide objective: knowing more about the customer at the end of the transaction. Big data can provide a clearer picture of the individual in front of the cash register, but to completely access the full spectrum of data available at point-of-sale and beyond, the leaders behind big data efforts will have to strategically approach their distribution and payment partners and determine how their data assets can be optimally combined. They'll need to understand what data they bring to the table and how it could be of use to their partners (and vice-versa) to fill in their respective knowledge gaps. Negotiation, strategy, and relationship building will be key skills in developing a win-win relationship among partners that will lead to the richest combination of data.
3. How should big data projects fit into our company's existing structure?
Because many CPG and retail companies follow the model of industry bigwigs like P&G and Unilever, chief data officers must decide where to position their big data projects. At the brand level? The product level? By geographic region?
To use P&G as an example, a leader of big data initiatives could partner with a brand manager and focus on analytics at the level of a particular brand or at the product category such as beauty, cleaning or baby products. While the data will obviously inform decisions across the organization, the executive will need to make strategic decisions about which roles to partner with in which departments in order to maximize ROI.
4. Think big: What could we accomplish if we had the right data?
Big data initiatives often focus on using existing data–data that companies and their partners already collect–and integrating it in new ways to learn more about customers, processes and products. But the most effective big data leaders will be able to tackle a new challenge that we're calling "applications conceptualization"–envisioning what could be done if the right data was available. This forethought requires a keen understanding of the business's objectives and a thorough understanding of what data is available and how it can be collected. Someone with this strategic vision must also be able to straddle the science/R&D and the marketing/sales functions–a critical skill in the new, big-data powered retail and CPG world.
5. How will you build and manage an effective team?
Retail and CPG companies that incorporate big data into their everyday operations have created teams around their projects, bringing together existing employees and new hires from a variety of different departments and backgrounds. We're increasingly seeing these teams composed of personnel from a number of different functions: market research, consumer insights and IT, among others.
But building the necessary depth of both analytics and industry expertise will be a challenge for all leaders in this space. In fact, universities are beginning to notice this skill gap: NYU has developed a graduate program within its Center for Data Science that trains students in math/statistics, computer science and data science, helping them establish a flexible foundation that can translate across industries. Chief data officers building teams around big data initiatives will need to understand how to best recruit talented data scientists and, once they're on board, how to pair them with employees with more industry expertise in order to create a team that can effectively tackle industry-specific challenges.
As brands and retailers begin to understand how big data fits into its transition from a cheap-to-market to a fast-to-market model, industry executives find themselves in unfamiliar territory. Historically, leaders in other industries have taken CPG's marketing and R&D tactics as gospel and emulated their strategies. But in the case of big data, the tables have turned, and CPG executives must look outside their sector for best practices and for potential leaders. Asking these five questions, carefully vetting candidates, and digging into their ability to apply data science to the specific needs of your company will ensure that you select an effective long-term leader.