Russell Evans of Nielsen on Analyzing Analytics

More and more data - what's a CG company to do? While the amount of information a manufacturer gets is on the rise, so is the challenge of turning that data into actionable insight. Russell Evans, vice president - Product Leadership Global Business Intelligence for The Nielsen Company, speaks with CGT this month, and provides his thoughts on how companies can successfully manage data through analytics today and beyond.


What are the top information challenges CG companies face? How can they be addressed successfully?

Evans: Our industry is confronted with ever-increasing sets of complex data combined with accelerated change in the full range of our business environment, extending from channels to consumers. Under these conditions, credible insights are more important than ever. Decision makers need to quickly sort through the information available to them and use it to make informed choices if they are to achieve a competitive advantage.

There is a gap between the amount of data we have at our disposal and the amount of data we actually utilize to make business decisions, and we refer to this as the "information ecosystem competitive advantage zone." This zone encompasses cost of data storage, harmonization, mining and maintenance. When a company is spending resources on any of these elements but is not utilizing all the available information, it has a negative effect on ROI. Companies closing the gap most efficiently and effectively will win in the marketplace, but their success hinges on a vibrant information ecosystem.

Many companies are working with the same data sources or the same types of data and little competitive advantage can be gained if the material is not enhanced in any significant manner.  In today's marketplace, challenges such as consumer fragmentation and channel blurring create an intricate business environment with rules that change frequently. This constantly evolving landscape makes it more important than ever to mine the data for unique insights and places a premium on effective analysis tools. Whether it's assessing promotional effectiveness or core consumer behavior, the right data can help deliver much-needed answers.

What are some best practices to leverage the data through analytics?

Evans: From a best practice perspective and in simple terms, the solution must make it easy for a user to discover an insight, share the information and take action to drive profitable growth. Analytical efforts and tools must help to drive profit, volume and share. This can be accomplished through actionable insights that result in optimal decisions.

True insights address not only the "what" of business performance, but also "why" it is performing the way it is, and "how" that performance can be influenced. For years, industry reports have been adept at explaining what happened. But to what degree does reporting enhance efficiency and value? If an information ecosystem is configured to predominately address the "what" of past performance, companies will risk spending a disproportionate amount of time and resources focusing on past events and will not be agile enough to address the upcoming challenges and opportunities in an optimal manner.

Companies must be able to get at the bigger picture by combining all relevant information in one place in order to get a complete view of the marketplace. Also, they must be able to view and compare disparate data sources to obtain a total picture of their corporate performance. The data residing in different applications should be completely accessible during analytics. We call this "application reach through." If information in a different environment is needed for analysis, we can reach out and pull that needed information to factor in our analysis. Additionally, as users navigate from one business issue to another, the application should offer what we call "context carry" -- seamless navigation that remembers the context of a particular analysis and feeds that context to the next analysis so that the user does not need to start from scratch each time.

Consistent guided analytics embedded within analytical applications are critical. They point all users in a company to one version of "the truth" and facilitate quick, well-informed decisions. These should result in the ability to capture market share by spotting and acting upon trends before the competition.

How can all of this information be used in everyday business applications?

Evans: First, the application has to be made simple and easy to use. Even the best application  will not reach its potential of adoption by a larger user base if it is not intuitive, well designed and user friendly. A consistent challenge that companies face is the rate of adoption of the technologies in which they have invested. Some of it relates to change management, but some of it is due to how simple or complicated it is to utilize the research tool.  Second, the application has to be robust and provide deep analytic capabilities for power users.

From a graphically intuitive usability perspective for our own software, we worked with companies in the United States and Belgium to design a better user interface (UI) that would provide the most meaningful data insights in the most efficient manner.  The application must support the ability for users to visually integrate and digest information quickly. The particular company we worked with, caught our eye because they helped design the gauge cluster of a new fighter jet and reduced the number of gauges from 20 to 30 to a single 3D gauge. We needed to bring this type of creative thinking to the CPG industry.

We  performed sophisticated usability testing that tracks eye movement and helps pinpoint where changes in the software need to be made. Our ultimate goal was to increase the number of people in a client company who can perform intricate data analyses and we have succeeded in making the applications convenient enough for everyday business users, but sufficiently robust to meet the analytical needs of the power users. We also added the capacity for shared views to facilitate consistency.

I already mentioned guided analysis, but there are other practical considerations that should be made. It is important that capabilities are organized around business issues, such as assortment, pricing, promotions and the consumer.

What are next steps once the right system is in place? What is the future of analytics? 

Evans: With the right ecosystem developed with an effective and efficient analytics component, additional data sources can be added by utilizing proper master data management (MDM) approaches. MDM is the initial and ongoing harmonization, and synchronization of data assets. For example, in a global context it provides multi-country harmonization with a consistent metadata layer. That broad integration capability allows the ecosystem to interoperate and keeps it healthy. The data will be more granular and constantly refreshed, enabling richer insights and quicker and better decision making.

We will see a continuation of channels blurring and consumers becoming further fragmented which will result in larger data subsets, but because newer systems provide faster data analysis, it will be easier to perform analyses more frequently. Ease of use will push the ability to analyze data deeper into an organization, and bring it closer to the end business user and decision maker. Analytics will be consistent across the organization to provide one version of the truth. We also see a much more pronounced focus on collaboration between trading partners.

We are already seeing increased personalization in our programming, media and publications. New venues to reach consumers, such as video games, are cropping up and mature venues, like in-store media, are being redefined. This gives us more granular data on consumers and their preferences. We see growth in a permissions based-approach where consumers will provide access about their preferences and purchasing habits to entities they choose in order to get better service. This will be enabled by the convergence of personal communication devices and ubiquitous connectivity between those devices and devices such as televisions and computers at home, navigation systems on the road and smart shelves, displays and other in-store devices at retail stores. Information at a personal level of what someone watched, how they shop, when they shop, where they shop and with what type of promotions will be available. Retailers and manufacturers must have the analytical horsepower to collaborate and tackle such granularity to have more specific targeting.

The future is going to be exciting for those who will be ready for it, and to be ready, the foundation of what is being used today has to be right.