In Accenture’s latest technology vision entitled “From Digitally Disrupted to Digital Disrupter,” the consulting firm provides an insightful tour d’horizon of trends occurring in the digital world and how they are going to affect businesses. The study’s cover asserts, “Every Business is a Digital Business.” Although that may sound a bit hyperbolic, the fact is that every business is somehow affected by data. The six trends identified in the report are: 1) Digital-physical blur; 2) From workforce to crowdsource; 3) Data supply chain; 4) Harnessing hyperscale; 5) The business of applications; and 6) Architecting resilience.
In this article, I want to focus on the third trend: the Data Supply Chain. The Data Supply Chain shouldn’t be confused with physical supply chains that move goods around the globe (although the flow of data is playing an increasingly significant role in the physical supply chain). The Data Supply Chain is about “putting information into circulation.” Analysts know that data and information are not the same things. Information (or knowledge or insights) is gleaned from data and that gleaning process is not as straight forward as many people believe. The study notes, “Data ecosystems are complex and littered with data silos, limiting the value that organizations can get out of their own data by making it difficult to access. To truly unlock that value, companies must start treating data more as a supply chain, enabling it to flow easily and usefully through the entire organization — and eventually throughout each company’s ecosystem of partners too.”
In past articles, I’ve written about the obstacles and challenges that siloed information can create for a company. The biggest challenge, of course, is that when various organizational groups use their own data sets they are working from different versions of the truth, which makes aligning corporate strategies difficult. Enterprise Resource Planning (ERP) systems have helped address this problem; but, much of the data available today is unstructured and, therefore, not integrated into many ERP systems. The study notes, “Data is the lifeblood of every digital organization, but businesses are struggling to access, share, and analyze much of the data they already have. Through 2015, 85 percent of Fortune 500 organizations will be unable to exploit big data for competitive advantage.” That is a surprisingly large percentage considering the fact that “business leaders now view data as among their most valuable assets.” The study concludes, “Business leaders now need to develop an end-to-end view of data in order to achieve their business goals.” The study continues:
“The data supply chain must enable data movement. And in order for data to move, it must be made visible and accessible to those who need it when they need it. As such, the first step is to create a data services platform or federated data access layer, which provides a standard method of access to an organization’s curated and trusted (albeit varied and siloed) data in a time-relevant manner. Currently, only one out of five organizations integrates data across the enterprise. But those few are realizing great benefits.”
The study asserts that, in order to achieve successful data integration, organizations must create a data services platform. It discusses a number of these platforms that are available from vendors. It concludes:
“In the end, there’s no one-size-fits-all solution; most enterprises will end up with a hybrid set combining many of these tools. But no matter what the solution, it’s important to understand that data access and data acceleration make the data services platform both possible and necessary — and thus help to realize the data supply chain at scale.”
The study goes on to note that fixing the data access problem isn’t enough. Business decisions are now being made within very short decision cycles and, therefore, the velocity of the data upon which those decisions rely must also be accelerated. As the study states, “Quick access to valuable data means that analyses can be performed, insights can be gained, and actions can be taken in the sometimes very small window of opportunity available to businesses.” Again it needs to be stressed that data needs to be turned into insights before it becomes useful for decision-making. The study notes, “The process of discovering new insights to answer business questions is changing fundamentally as users get faster access to more data.” It goes on to state, “Data discovery empowers users to ‘communicate’ with data at close to the speed of thought — accelerating businesses’ time to insight. Companies can and should be investing in this practice today.”
When it comes to data discovery, the Accenture study asserts that the next step is cognitive computing. “As the volume and variety of data grow,” the study reports, “so too do the scale and complexity of the data supply chain, making it increasingly difficult to add to and get value from data as it is manipulated.” It continues:
“What if … machines could be taught to leverage data, learn from it, and, with a little guidance, figure out what to do with it? That’s the power of machine learning — which is a major building block of the ultimate long-term solution: cognitive computing. Rather than being programmed for specific tasks, machine learning systems gain knowledge from data as ‘experience’ and then generalize what they’ve learned in upcoming situations. Cognitive computing technology builds on that by incorporating components of artificial intelligence to convey insights in seamless, natural ways to help humans or machines accomplish what they could not on their own. At its most advanced, cognitive computing will be the truly intelligent data supply chain — one that masks complexity by harnessing the power of data to help business users ask and answer strategic questions in a data-driven way.”
Clearly, the most famous system associated with cognitive computing is IBM’s Watson that beat human champions on the game show Jeopardy! IBM is beginning to build a practice around Watson because, like Accenture analysts, IBM executives believe cognitive computing represents the future. As President and CEO of a cognitive computing company, Enterra Solutions®, you know that I see things the same way. I’m gratified that the Accenture study discusses a case study in which Enterra® plays a significant role. It states:
“One interesting cognitive computing example comes from U.S. food company McCormick. Machines are now starting to use data to ‘sense’ the world as humans do, and this extends to taste — with obvious benefits for the food industry. Using Enterra Solution’s Cognitive Reasoning Platform, McCormick’s FlavorPrint site asks customers to rate a variety of flavors in order to learn taste and, from that, creates unique taste preference profiles — or what it calls FlavorPrints. If customers provide additional information, such as cooking preferences, equipment, and typical pantry items, they can receive better personal product and recipe recommendations. As far as these customers can tell, they’re providing just a few raw facts in return for a great deal of personalized value about taste — something almost everyone feels strongly about yet finds hard to quantify or specify. From McCormick’s point of view, learning customers’ taste preferences leads to better insights, product decisions, and, ultimately, ability to serve its customers.”
As the study implies, there is a lot happening behind the curtain when a customer answers a few questions about taste preferences. McCormick’s use case demonstrates that only the imagination limits the potential uses of cognitive computing. The Accenture study concludes:
“Cognitive computing can, and will, bring benefits to many industries, and it will fundamentally change the ways in which many businesses operate. It flips the problem of data volume and variety on its head and instead leverages it to enable the smart, interactive data supply chain. The ultimate goal is for any business user — from a CEO to a field worker — to be able to ask any business question and immediately get a data-driven answer from the masked data supply chain. Although this technology may seem far off, there are already cases that prove its relevance. And by its very definition, with more data over time, cognitive computing technology will only learn more, adapt quicker, and improve. It’s important for business leaders to familiarize themselves with this technology now.”
If, as the study asserts, every business is a digital business, then eventually every business will come to appreciate the value of cognitive computing. Cognitive computing systems don’t just crunch numbers they apply common sense to analytics so that insights are more informative. We are on the cusp of an era in which cognitive computing systems will help business leaders make better decisions within the compressed decision cycles they now face. Enterra Solutions is ready to help.