Businesses Need to Leverage Smart Data

Stephen DeAngelis

September 26, 2019

Data is now considered the world’s most valuable resource and companies wanting to gain the greatest value from that resource need to do more than hoard it. We are getting very close to the day when the term “big data” falls into disuse replaced simply by the term “data.” There are a couple of reasons for this turn of events. First, databases are getting so large the term “big” seems anachronistic. Second, businesses are rapidly learning data quality is more important than data quantity. Don’t misunderstand me, data quantity matters; however, lots of bad data isn’t worth very much. Kimberly A. Whitler (@KimWhitler), an Assistant Professor at the University of Virginia’s Darden School of Business, explains, “‘Big data’ isn’t as important as ‘smart data’ or the ‘right data.’ Companies are getting excited over the notion of big data, but it’s ultimately only as good as the insights you get out of it.”[1]

Whitler’s point may be obvious; nevertheless, it’s important. The value in data must be extracted like gold from a mine. The “miners” performing this extraction are cognitive technologies, like the Enterra Enterprise Cognitive System™ (AILA®) — a system that can Sense, Think, Act and Learn®. RJ Frometa (@rjfrometa) explains, “[Analyzed big data] helps businesses to understand their competitors better and take much more informed decisions. Big Data is basically raw data that comes in structured and unstructured forms. The structured [data] is very user friendly and simple to examine while unstructured [data] is comparatively difficult to examine.”[2] Cognitive technologies can handle both structured and unstructured data and can help transform big data into smart data.

Identifying the right data

What constitutes the “right data” is unique for each enterprise. Whitler explains, “Companies today are more often than not starting with the data and seeing what they find. It’s equivalent to finding a needle in a haystack. Start with the business drivers, the fundamentals and the strategy, and work backwards to figure out the best data sets that uncover the insights you need to help steer your direction. The technology that is allowing us to understand big data is great, but only when it’s paired with domain expertise does its true value really come through.” Kalev Leetaru (@kalevleetaru), a Senior Fellow at the George Washington University Center for Cyber & Homeland Security, observes, “It has become an unfortunate trend of the ‘big data’ world that we focus on the size of the datasets we analyze, rather than the number of useful datapoints they contain or the insights we gain from them.”[3]

In a separate article, Leetaru writes, “Instead of focusing on petabytes or exabytes or trillions of rows [of data], the answer to what constitutes ‘big data’ lies in what we do with all of that data. … In the end, shifting our gaze from how much data we hoard to what we actually do with all of that data would go a long way towards moving the field from meaningless marketing buzzword towards genuine business insights.”[4] In other words, one really can’t talk about the importance of data without highlighting the importance of analytics. Saranyan Vigraham, vice president of engineering at Petuum, puts it this way, “Data is not equal to knowledge, or more precisely, not the knowledge you think it equals.”[5] He adds, “A common pitfall a lot of machine learning (ML) companies run into is mistaking data as knowledge. Several enterprises think that having a lot of data makes them ripe for harvesting insights instantly through AI and ML techniques. It is not entirely true.”

Leveraging smart data

As noted above, the right data for a business depends on the business. Analyze the right data and you get smart data. Smart data can improve maintenance, track assets, and serve customers. Miah Hammond-Errey (@Miah_HE) writes, “The exponential growth in data combined with increased computational power and storage capacity has enabled advanced analysis and is driving a new kind of social change.”[6] She adds, “Big data analytics have been presented as the panacea for information overload and big data itself as no less than transformative and world changing. In their 2014 book, Viktor Mayer-Schönberger and Kenneth Cukier emphatically declared that big data ‘will revolutionize the way we live, work and think’. Commentators have praised big data as the new oil of the 21st century, the world’s most valuable resource and the foundation of all of the megatrends that are happening today, from social to mobile to the cloud to gaming.” Hammond-Errey goes on to note data can be abused as well as used. Most of her concerns surround the use of personal data rather than industrial or business data. Companies need to understand how data can be leveraged and how it can be misused. Proper (i.e., ethical) use of data can benefit companies in numerous ways, while misuse of data can risk a company’s future.

Much, if not most, of what is written about big data analytics focuses on customer-facing uses. For example, Frometa discusses four ways smart data can help businesses: Improving cost effectiveness; understanding customers; understanding market conditions; saving time; and providing a competitive edge. He concludes, “Businesses [that] have not used the services of Big Data are missing out big time. Not only does Big Data offer companies … a thorough understanding of their customers, it also offers amazing growth and development opportunities through analyzing the vast amount of data that they have stored.” Whitler suggests doing three things to convert big data into insightful and actionable smart data. They are:

1. Make decisions at the speed of business: Whitler writes, “Technology is changing so rapidly and data is multiplying so quickly that it’s really important to understand that what you have will never be perfect. Make sure you have the ability to revise and update and refresh and just move.”

2. Celebrate Collaboration: “In order to do this right,” Whitler writes, “you have to be open to partnering and creating a network, or team of companies that is going to help you be successful. There is not one company that will give you everything you need. And if you wait to perfect it internally, you’ll miss out because your speed and agility won’t be able to keep up.”

3. Create a Playbook: “Although no data set is exactly the same, and each set will likely uncover unique insights,” Whitler explains, “creating a playbook on how to arrive at smart data can prove useful for future initiatives that center on big data. Creating a playbook is also a sure way to help socialize and familiarize the big data to smart data conversion process among your teams, as well as across your company’s greater marketing function.”

Concluding thoughts

The bottom line is: Smart data is data mined for insights by cognitive technologies. The kind of data that is mined and for what purposes varies with every organization. For the most part, the end result will be insights that improve enterprise decision-making. Vigraham suggests human inputs remain important in the decision-making process. He recommends most system solutions be designed with expert humans in loop. Good decision-making begins with good data. Although the size of databases can be important, having the right data in the right amounts is even more critical.

Footnotes
[1] Kimberly A. Whitler, “Stop Focusing On Big Data And Start Focusing On Smart Data,” Forbes, 20 August 2019.
[2] RJ Frometa, “What is Big Data and how can it give you an advantage over your rivals?Vents Magazine, 30 July 2019.
[3] Kalev Leetaru, “Big Insights Not Big Data: Why We Should Stop Talking About File Size,” Forbes, 9 January 2019.
[4] Kalev Leetaru, “Is ‘Big Data’ About What We Do With Our Data Not How Much Of It We Have?Forbes, 16 June 2019.
[5] Saranyan Vigraham, “Data Is Not Equal to Knowledge,” Manufacturing.net, 4 June 2019.
[6] Miah Hammond-Errey, “The transformative potential of big data,” The Interpreter, 24 June 2019.