#71 – BRANDS, QUALITY, AND CSR – KELLY EISENHARDT

Kelly EisenhardtBig data analytics are changing the way companies manage brands, monitor the quality of products, and measure the efficacy of corporate social responsibility programs. Social media has driven data creation exponentially. Google Analytics tells us that fourth-fifths of all new data is unstructured and growing at 15 times the rate of traditional enterprise data. More data is created in 2 days than was created before all of 2003.

Daniel Di Benedetto is Vice President of Operations for Aitellu Technologies AB, a company based in Gothenburg, Sweden. Aitellu from the words “artificial intelligence tells you,” focuses on helping companies make profitable and insightful decisions for brands, quality, and corporate social responsibility using powerful big data capabilities that leverage artificial intelligence and genetic programming software.

What is the biggest problem with regard to the volume of the data that is generated daily?
The biggest problem is data that is created outside of company walls. External data is increasing fast and leaving companies vulnerable to public scrutiny regarding their brands, products, and practices. It’s difficult to stay ahead of the trends or predict risk accurately with traditional business intelligence tools in such a rapidly evolving environment. Not having access to the right tools inhibits the ability to make swift decisions when a course correction is needed.

How have companies managed this vulnerability in the past?
Many companies focused on internal enterprise data. There was no strategy around how to incorporate the data being created external to the company. The biggest vulnerabilities lie in data created on social media platforms, Amazon ratings, and online communities. It has direct impact on brands, product positioning, and corporate social responsibility to name just a few areas.

Why is the volume of data an issue?
It’s not the volume of data but the ability to collect, analyze, and find anomalies that pinpoint current situations and predict and prevent future issues. Transforming the data into accessible, readable, and actionable information in real-time is the challenge.

Structured data is too costly to build and maintain and does not provide enough value to the end user. It leaves gaps when trying to understand what is really going on in the market.

What are some of the disadvantages of structured data?
There is no point in structuring all of the data when today’s technology can read unstructured data and provide insights that transform it into actionable information. Why spend so much time and money to structure it when it can be read in its native form already? It’s not practical based on the volume created daily. Companies need to be able to pull the most salient points quickly, identify the trends or potential issues, and move toward a more beneficial path.

Are you saying there is no need for structured data?
No. I’m not saying that. In the past, we needed to look at one hundred points of discussion and today, it’s thousands. Smart tools make sense of volumes of data and help companies review patterns and history. We can monitor and measure volumes of information that may represent something a company didn’t know before. There are systems that are really good at reporting structured data and creating visualizations that present an important point of view. Our tools manage both structured and unstructured data. Critical decisions are made by looking at the whole picture.

In addition to traditional business intelligence tools, what might big data analytics tools look like?
There are three elements to a big data system in addition to traditional business intelligence tools.

The first component is the ability to spider or crawl through the data so that when a company is asking a specific question about its market, products, or customers, it can get back answers and transform them into actions.

The second component is to interpret the sentiment in rating systems and comments. An ability to decipher whether a positive or negative rating is given and why is meaningful. Keywords and geographies are associated with sentiment ratings which enable actions. This helps determine trends and where information is heading. It prevents a scenario where the negative trend becomes part of history and can no longer be acted upon.
Third, aggregation leads to the visualization of the data. The data needs to be turned into insights. Companies need to visualize and understand what the data is saying in a quick and clear manner. Different people within the company need to digest the information in different ways. An operations manager has a different directive and view than the CEO. A supply chain and compliance person sees things differently from the sales team. They need data that aligns with their role in order to act upon it.

Can you describe some of the opportunities that a business can gain from big data analytics?
Product positioning is a top concern. Companies want to predict which products will sell the best and to which markets. When releasing new products, the focus is on psyching up the market by creating a perceived need. When people hear the hype, the first thing they do is a Google search. A community of people then decide if the product is something they want to spend money on. They discuss it through social media outlets. All of that externally created product and user data is available to companies if they look outside their walls.

Quality is another area companies struggle with daily. Quality is about long lasting relationships with customers. Bad quality is a risk to a company’s brand and a gift to the competition. Listening to the customer is crucial to identifying potential problems before they spiral out of control. Spotting quality problems early is important. Companies don’t want their loyal customers looking for better alternatives or downgrading their brand. It takes time to regain trust and rebuild a brand. Consumers will go to competitors. Big data analytics is extremely helpful in predicting this as well as incidents like potential expensive recalls.
Finally, the whole world is very aware of environmental and social issues. With ears to the rail, big data follows all those trends. It’s critical to have the best and fastest access to information about compliance and sustainability. It’s imperative to know the impact on brands.

Promoting products as “green” generates social media discussion. What happens when consumers are talking about the forced labor issues in stevia harvesting or the deforestation associated with palm oil, or expropriation of water rights? What about the recent “land grabs” where farmers are being bought out from family farms and forced off their lands by large corporations? If it is discovered that child labor is being used in your supply chain because someone is talking about it on some form of social media, how do you get ahead of it, collect enough information about the truth, and put an action plan together in the shortest amount of time? The damage is done. Topics like these bring out people’s passions for the products they buy.

With all that you know, how can big data trends and analytics help companies be more profitable and better corporate citizens?
The total explosion of big data affecting your product and your market has just begun. I expect in a few years all companies will need something to help them navigate the three areas I mentioned. This is the foundation for increasing revenues, keeping costs contained, and being a positive contribution to the evolution of the world. If companies want to stay competitive and in the forefront, they need to facilitate any activities, processes, and tools that support their competitive strategy. A digital strategy needs to be implemented for how they will manage external data and the intelligence that comes from it. Companies need to be data driven before they are product driven. People don’t know what to do because often, they don’t know what they can do.

Originally published in Energy Pro.  (C) Kelly Eisenhardt.

Bio:

Kelly Eisenhardt is Co-Founder and Managing Director at BlueCircle Advisors, an environmental compliance and sustainability consulting and training firm based in Massachusetts (www.bluecircleadvisors.com.)  In her role at BlueCircle Advisors, she is responsible for providing business intelligence, strategy and implementation of environmental, social and governance (ESG) risk programs.  Her experience aligns well with her client’s needs for technology, compliance, and sustainability expertise by helping companies create and manage their corporate environmental and social responsibility programs.

To contact Kelly Eisenhardt, send emails to kelly.eisenhardt@bluecircleadvisors.com or follow her on Twitter @KelEisenhardt.  For more information about BlueCircle Advisors and the company’s products and services, please visit www.bluecircleadvisors.com, on Facebook at BlueCircle Advisors, on Twitter @OurBlueCircle, and on the LinkedIn group at the BlueCircle Advisors group.

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