"The term big data is moving up the charts as a 'hot topic,'" writes Lora Cecere, Founder and CEO of Supply Chain Insights. She continues: "We believe that the adoption of new concepts for big data is a step change for supply chain teams. It is not about force-fitting new forms of data into applications based on relational databases. It cannot be treated as an evolution. It requires change management. It is about small and iterative projects using new forms of analytics. The projects have to be based on a business problem and the focus needs to be on continuous learning." ["Welcome In the Big Data Opportunity," Supply Chain Shaman, 9 July 2013] Clearly, Cecere sees big data as a tool in the problem-solver's kit. She begins her article, however, with a graphic that shows that 12 percent of respondents to a recent survey her firm conducted see big data a "big problem."
I obviously agree with Cecere that big data offers significantly more benefits than problems for companies that apply analytical techniques wisely. I was also pleased to note that Cecere sees my company, Enterra Solutions, as one of the firms on the cutting edge of providing big data solutions. She writes:
"To drive success companies have to sidestep the hype. While the powerpoints on big data concepts abound, very few technology companies and consulting partners have built solutions to harness this opportunity, and even fewer supply chain leaders are ready to have the discussion. We find the work by Aster Data (now a division of Teradata) and the work by IBM and Enterra Solutions on cognitive learning engines to be promising. We are also encouraged by SAS's work on unstructured text mining, Bazaarvoice on the translation of blog and sentiment data, and the work by APT on test-and-learn strategies is exciting. We are also encouraged by the work on cold chain and serialization by a number of consultants working on sensor data and counterfeiting."
From her comments, you should begin to understand that the uses of big data analytics can't be easily pigeon-holed. They have a broad range of applications for solving business problems. Cecere believes the "biggest opportunity" involves the management of "new forms of data." Lisa Kelly agrees with Cecere that "the growth of data – both structured and unstructured – will present challenges as well as opportunities for organisations over the next five years." ["Big data and analytics: a large challenge offering great opportunities," Computer Weekly, 8 July 2013] Kelly continues:
"With growing data volumes, it is essential that real-time information that is of use to the business can be extracted from its IT systems, otherwise the business risks being swamped by a data deluge. Meanwhile, competitors that use data to deliver better insights to decision-makers stand a better chance of thriving through the difficult economy and beyond. The aim is to be able to use real-time data for real-time decision-making to become a real-time business."
Dave Lounsbury, chief technology officer at The Open Group, told Kelly, "Mobile devices, social networks and real-time information are driving big data – be prepared to handle this by developing competence in data architecture and analysis tools. Business leaders know that the ability to get and understand competitive data is gold dust, and they will be knocking on your door requesting it." Kelly asserts, "Treating big data as a problem which must be addressed is misguided." She continues:
"For big data to achieve insights which deliver real results, it is essential to understand what the business is doing. 'Big data needs to add significant value,' says [Suranjan Som, head of the business intelligence practice at Information Management Group]. 'For example, if it is in the online space, you need to understand what data is doing beyond the website – and must extend to social sites, such as LinkedIn and Tweets, so you get to know your customer better and can sell up, or in different ways.' A predictable use and growth pattern of big data can't be foreseen over the next five years, but it is important to make forays now to understand what is involved. 'The traits of big data are varied data types, speed of growth or velocity, and volume with billions of rows,' says Andrew Logie, CTO at consultancy DrPete. He says key issues over the next five years will be securing data; issues of locality, privacy and regulation; human resources; and project requirements."
Kelly concludes, "Uses for big data must be democratised to support real-time decision-making, or it has no future." By that she means that applications must be developed in such a way that ordinary users, not just computer experts, can use them and derive valuable and actionable insights from big data.
The supply chain is not the only area where big data analytics is viewed as tool in the problem-solver's kit. Erika Poole, Event Coordinator at MassTLC, summarized some of the discussions held during a recent MassTLC-sponsored Big Data Summit, entitled Quantified, Connected, Predictive: How Data Analytics Will Transform Our World. ["How Data Analytics Will Transform Our World," MassTLC Blog, 8 July 2013] Participants were divided into four interactive discussion groups: Connected Health; Transportation; Personalized Medicine; and Data Mashups. Summarizing the first group's discussion, she noted the following challenges:
"In order to gain access and analyze the data without patient approvals, the data has to be made anonymous. Next, the variety of data in healthcare is a massive challenge. Lastly, integrating the data and having a view of all data from disparate systems is critical to making sense of it to improve care."
Despite the challenges, however, Poole notes that participants "agreed that if you can show REAL business value to the doctor and patient to help improve care and lower costs, access to the data and overcoming the security and integration issues will happen." When summarizing the next group's discussion (i.e., transportation), Poole notes that this sector is already using big data analytics extensively. She reports that panel members concluded, "Transit is big data.” They predicted, "Within two years we will see a whole new experience of what we can see in our cars, such as Vehicle ID, Safety, and fleet optimization." Panel members also expected big data to be used more extensively by local governments to "provide transparency to the residents that their city is doing their job, and further help it to compete economically and socially."
In the discussion group involving personalized medicine, there was some debate about exactly what the term meant. Most participants appear to have agreed that it involves "a medical model that proposes the customization of healthcare - with medical decisions, practices, and/or products being tailored to the individual patient." I'm assuming big data is involved through the integration of health records, patient diagnoses using artificial intelligence, personalized drugs created by genome analysis, and so forth. Poole reports that participants "shared solutions that exist in the market today and forward thinking ideas that can help tailor individual treatment plans for patients."
The final discussion group (i.e., the data mashups group), discussed "how companies can extract value from the multiple types of data." Poole reports:
"A major theme that came from this session was customer care. You must be aware of what your customer wants and needs and, utilizing numerous types of data, [big data analytics] can provide you with those insights. ... Just monitoring social media is not enough, service providers need to take action. In today's world, organizations can personalize to their customer base and provide a truly great experience leading to retention. ... Organizations must know the questions they want answered in order to create true value from the data."
I certainly agree with that last point. To learn more about that subject, read my post entitled Big Data Analytics: Good Questions Result in Better Answers. Are there challenges associated with the use of big data? Of course there are. All of the pundits cited above agree on that point. They also agree that the opportunities presented by big data analytics make working through those problems worth the effort.
