EXPERT ANALYSIS
SECTION ONE
SECTION TWO
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Big Data Getting Bigger
Big Data is getting bigger, says a recent IDG Enterprise survey of over 750 IT executives. Almost
50 percent of respondents say they’re implementing Big Data projects, or are planning to. Good News:
More than one of five execs say their projects have improved both the quality and speed of decision-
making. Bad News: About four of ten respondents say finding the right people for Big Data initiatives is a major challenge.
DISCUSSION QUESTIONS:
Based on your experience and/or observation, what is the biggest benefit or advantage of Big Data? What is the biggest challenge? How would you sum up the state of Big Data usage in the CPG/retail industry?
EXPERT ANALYSIS:
The biggest benefit of Big Data is the opportunity to develop greater and greater consumer intimacy. Leveraging existing and emerging data types to understand consumer needs and preferences, and assess behavior and monitor changes in perception can help CP companies reach, engage and serve consumers with highly tailored, timely and relevant content delivered consistently across both physical and virtual channels. CP companies that can both develop deep consumer intimacy and deliver compelling consumer experiences while consistently maintaining consumer trust will be in the best position to build consumer loyalty, ensure repeat purchase and accelerate development and delivery of new consumer-driven innovations to drive sustainable growth and competitive advantage.
The biggest challenge is actually two-fold. First, the volume, variability, velocity and granularity of data continue to increase. The volume of available data is increasing exponentially to include retailer point of sale data, retail measurement syndicated data, supplier inventory data, real-time manufacturing capacity and inventory data, social media monitoring, periodic consumer research, and more. These data elements are all available in variable formats and at different velocities; that is, real-time, hourly, daily, weekly, etc., making data integration and lifecycle management especially challenging. And, what’s more, data is becoming more granular, creating opportunities for analysis and planning against, for example, increasingly refined segments of consumers, region-specific seasonal SKUs, and more. While access to this data provides newfound opportunity, there is great challenge in harnessing the vast volumes of information, and harmonizing it to gain insight.
Second, the definition of Big Data is constantly evolving. The coming age of the Internet of Things will create even greater volumes of real-time streaming data interactions between sensor-enabled devices, machines, locations and consumers. What’s more, marketers are now also learning to combine objective transaction data with subjective information gleaned from social media monitoring, social sentiment analysis and consumer research. Armed with this information, for example, companies can track positive or negative changes in consumer perception of a brand in response to a promotion, price or packaging change, or other market factors that might influence perception such as on shelf availability.
Maintaining a clear understanding of and strategy for Big Data, and making sound decisions about how the various elements of Big Data available to the enterprise can be used in conjunction (or contrast) with each other to derive real business value, is no easy feat.
The Consumer Products industry is just beginning to scratch the surface of the enormous opportunity that Big Data represents. Many CP companies have begun developing more comprehensive strategies for managing Big Data, including acquisition, harmonization, and lifecycle management, while taking into consideration the evolving definition of Big Data and how its role and uses will continue to change. However, deriving significant and consistent strategic value from that data remains early stage. Only as companies begin to adopt the view that managing Big Data is less a “strategic outcome” and, rather, more a “strategic orientation” will the industry will begin to realize the even greater opportunities for driving real business value from Big Data that lay ahead.
Mark Osborn, Global Lead, Consumer Products Industry Marketing, SAP
Even as Big Data continues getting “bigger” and the opportunities for using it to address business issues expand, usage in the CPG/retail industry is very much in its infancy. While there is no question that trading partners already recognize the value of Big Data and are eager to mine it, they are challenged - both internally and externally - in employing it to drive faster and better decision making.
From the “outside,” available personnel trained on data products and experienced in data science/analytics is currently in too-short supply. The highly technical aspects of processing, mapping and analyzing massive amounts of transaction data require that significant systemic functionality be in place.
At the same time, many brands and retailers have a great deal of work to do educating internal constituents regarding the best application of Big Data. Those companies that succeed in building internal consensus and are effective in prioritizing and focusing related organizational resources will be the first to recognize return from what is arguably one of the biggest benefits deriving from Big Data - the availability of “microdata.” With access to data on granular levels that did not previously exist, brands and retailers can gain new insights to inform future actions. And, “win.”
Shari Wakiyama, Director, Business Intelligence, Inmar
Yes, Big Data is getting bigger, of course. But to say the 50% of respondents are implementing “Big Data projects” would depend on how those respondents are defining Big Data and who those respondents are.
How each company defines their “Big Data” project varies tremendously. Some companies think if they have a Facebook page they have a “Big Data project.” Others think if they are using point of sale data, they have a “Big Data project.” Some think if they are building a data warehouse, they have a “Big Data project.” Some think if they are advertising on social media, they have a “Big Data project.” Some companies confuse e-commerce sites with “Big Data.” Some think if they are implementing Hadoop, they have a “Big Data project.”
Most technology companies would say that less than 2% of companies have a true Big Data project. But that’s because most technology companies are looking at unstructured data. If you want to be completely accurate about it, true “Big Data,” as defined by companies like Google, would be projects that used unstructured data. Of the companies we work with, there are only two that I would say have a true
“Big Data project.” So my estimate would be much closer to 2% than 50%.
That said, most companies are still trying to get a grip on integrating internal and external data sources so they are harmonized. There is plenty to tackle with that scenario alone. Companies need to walk before they run. But that doesn’t mean they ignore social media or e-commerce. It just means they have to define projects correctly, put the right infrastructure in place and have a long-term plan that will also deliver short-term results.
Janet Dorenkott, VP and Co-Founder, Relational Solutions
Benefits/Advantages of Big Data:
- Ability to anticipate customers’ needs and take actions along the customers’ buying journey to influence the purchasing probabilities. However, buyer’s journeys in today’s world are multi-touch, multi-channel and multi-device, which makes it increasingly complex to decipher a customer’s buyer path. Big Data and smarter analytics allow you to profile them in a predictive manner so that you can engage in an almost one-to-one manner.
- Ability to innovate customer-centric value propositions and products based on social intelligence and chatter. Smarter analysis of unstructured social media data allows you to uncover the brand and product sentiments of your customers and segment them in terms of product propensities, geographic pull and brand potential.
- Ability to personalize the inbound communications and content to customers visiting your digital properties as well as personalize the outreach that leads to meaningful actions from your customers. Prior purchases, their location, their demographics, and their search process prior to landing on your website lend tremendous insights into the intent and motivations of your website visitors when analyzed with specific conversion goals in mind.
- In the CPG space, Big Data can enable effective collaboration with retailers. An inordinate amount of competitive advantage can be reaped when market research, market trends, brand development and consumer insights data from the CPG players are combined with the retailer tracked loyalty, transactional and demographic data on customers. Smarter analytics based on these data streams could lead to CPG firms innovating and marketing better products, retailers servicing their customers with the right promotions and value propositions and customers getting the benefit of the right product at the right price and through the right customer buying experience.
Challenges with Big Data:
- The biggest challenges that organizations face are around the lack of certainty on where and how to begin taking advantage of Big Data. There is an ongoing challenge to identify the right analytics to build and execute on that enables organizations from go from the state of “data deluge” to the state of “actionable insight” that is tied to a specific “business outcome.” Connecting these dots is an exercise that requires data intelligence, analytics intelligence, and contextual (business) intelligence.
- Data integration - ability to combine different varieties of data coming in from different sources and in different forms in a manner that can enable generation of connected and cohesive patterns.
- Lack of Skills - Ability to hire, retain, manage and generate value from a mix of the right skills that can bring together the data, analyze it and present it in a form useful for the business decision makers.
Conclusion:
Firms that will eventually build a sustainable competitive advantage based on analytics are those who are able to continually take the most optimal path directed by a closed-loop analytics framework in a dynamic environment. Those who begin with the end goal in sight and then work backwards to create the right data and analytics frameworks and align those with the right value drivers will be the ones to get past this data deluge.
Phani Nagarjuna, Founder and CEO of Nuevora
Big Data is both a blessing and a scourge. It is a blessing because food businesses can analyze and better understand what consumers are doing…at home, in store, or on-line. It can let food companies make more effective and efficient decisions about what products should be in the stores and what promotions should be run.
A study recently presented at the Promotion Optimization Institute meeting in November claimed that over 75% of all trade promotions failed. This was a massive study based on millions of trade events and zillions of data points. Using both the large amounts of data that are collected hourly across the country and statistical modeling, a business can estimate much more accurately how effective a trade promotion will be.
Retailers can control spoilage by examining when in the day various fresh foods are purchased and schedule deliveries around those times rather than ordering for the week and hoping someone buys it. The days of “mass marketing” are over; that is, ordering and going to Mass on Sunday and praying someone buys it!!
Big Data will be as important to food marketers as the microscope was to science. It gives the user a more magnified view of the world and the relationships that appear in the magnified environment. I believe that more uses of data will come about because of our ability to analyze it just like the microscope has given rise to a myriad of uses never anticipated.
But as my mother said, “I never promised you a rose garden.” The use of Big Data comes with obstacles and at a cost. The main obstacle is a lack of initiative to change. It is the digital natives that see Big Data as just another issue and no big deal. Management has been doing things the same way for years and is reluctant to change, Maybe one of the reasons for the reluctance is the cost. It is not cheap to implement these programs, and while the promised return can be substantial, the out-of-pocket costs can be high.
However, that might not be the biggest problem. Finding educated people who understand the food industry and are not just statisticians is a problem. While universities have added various Business Analytic programs, the grads are being gobbled up. These new types of employees have a higher cost in terms of salary and the learning curve. The analogy is similar to the beginning of computers. IBM needed programmers, but there was no profession called “programmer” in the beginning. They had to define the career and the skills needed.
Companies and universities will have to find data scientists who can take immense amounts of data and turn it into insights and answers. When they do, business analytics and Big Data will be as common to a food company as programmers are to the computer industry.
The question is not whether Big Data will be around in the next ten years, but how much will Big Data change the very fabric of the way food companies go to market.
Dr. John L. Stanton, Professor of Food Marketing, St. Joseph’s University
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SECTION THREE
