Business Enterprise’s Big Data Challenge

The fundamental challenge facing Business Enterprise with respect to the Big Data Movement is the fact that “the cloud” in presently an ineffective method for data transfer and information sharing. Business Enterprise has data security challenges that the average consumer does not. For example, let us consider a computer chip manufacturing company. This example company is in control of proprietary information related to the technologies they use to manufacture computer chips. They safeguard confidential data relating to their inventory, production, and financial performance. And, they have other plant data stored on their network, which is protected under stringent data security controls. The adoption of cloud-based technologies is not a viable solution due to the threat of data security breaches and outside threats to hack or otherwise compromise invaluable data. Heck, some of these companies are so tech-savvy that they have proactively implemented wireless interference tools to render one's cell phone unusable upon entering a facility. Therefore, “the cloud,” is simply not a viable data solution for most Business Enterprise customers (think energy and manufacturing operations, such as oil refineries, chemical plants, electrical utility, and the like).

Before I discuss the solution that I envision, let us examine the data transfer and information needs of such an energy or manufacturing operation. After all, operational efficiency that involves plant data has wide-ranging impacts for all plant disciplines at such a facility. Most databases utilized in the plant environment are disconnected data systems (I call these “data silos”), which require manual data input. Worse yet, some enterprise applications require one or more administrators to manage. These circumstances represent significant cost impacts for data management, and, very simply, this reduces profitability.

Beyond profitability, such a manufacturing facility will rely upon its "knowledge workers" (a term referenced from Bill Gates' Business @ The Speed of Thought) to perform tasks that can be automated, but are not yet because the tools in use have been trusted for the last 20, 30, or more years that the company has been in operation. This is the old “if it ain’t broke, don’t fix it” mindset (stay tuned in future blogs when I expound on how this old adage is the pandemic of a complacent society). To remain competitive in a global economy, however, Business Enterprise must proactively implement technology to optimize its operations, which inherently means automating every task that computers can do – thus, leaving "knowledge workers" to make decisions that computers cannot handle (so-called “judgment calls”).

There are profound impacts to technology adoption and automation that affect good manufacturing practices as well as safe work practices. Quite frankly, the risk of managing data in antiquated systems presents safety and manufacturing risks that can, and do, lead to regulatory violations, as well as, worker exposure to health and safety risks. This is a microcosm of where the industry is today - look no further than the critical datasets managed by many, large manufacturing facilities in a Microsoft Excel™ spreadsheet. In today’s world of sophisticated databases and network servers, this is an UNacceptable format for any critical dataset.

So, what is the solution? I believe that it involves bringing “the cloud” inside of the security firewalls of the owner-operator. In the above example, I believe that it involves “intra-virtualization” of the data management systems used at that computer chip manufacturing facility. I believe that it doesn't require a new application or interface; but the key will be database integration, in combination with software delivery tools to facilitate data transparency and render more efficient processes. I believe that it involves a common file format not called paper, which is the bain of a Business Enterprise that subscribes to processes that are unprofitable, inefficient, and risk-maximizing. I believe that we have developed the solution at Ei, and it’s only a matter of time before we help Business Enterprise overcome the Big Data Challenge.

Shane E. Kling