It seems every organization has its own definition of what Enterprise Intelligence might be – some organizations claim it is an educated work force, others may say it is an application such as business objects or Microsoft analytics reporting capabilities, the SASS or Cognos or whatever other applications people use for data analysis. Some organizations claim Enterprise Intelligence is the ability to put their metrics on big screens so everyone has visibility to the overall health of the process. Some people say it is the historical data that they have, the equipment level data or the product level data, or that it is the customer data that really encompasses Enterprise Intelligence.
I have concluded that it is all of the above and more. It is really about turning all of that data into value. We have found that, independently, none of these aforementioned claims really create value. It is only when one can obtain appropriately contextualized data, through the appropriate medium and couple it with the right technologies and business systems, can they really start to turn that data into prime value for the organization. Because of this, I prefer to define it as:
“The Execution of a Technological Strategy enabling integrated process and environmental knowledge to be leveraged in standard practices to accomplish operational excellence.”
When I refer to “environmental knowledge” in this definition, I refer to all of the environmental knowledge – the individual employee knowledge, the experts on the particular process, the product and manufacturing data and market data. By pulling all that data together and leveraging it into standard practices, you can achieve operational excellence.
In a 2012 survey the question was posed which were the most important challenges that faced organizations’ supply chains. At the top of the list sat product launches followed by increasing portfolio complexity and regulatory scrutiny.
There is evidence that key business drivers impacting manufacturing are innovation, followed by manufacturing agility and manufacturing complexity all while being required to maintain regulatory compliance.
So, what does this really mean? It means companies really have to provide better products (which are more complicated to manufacture) and we need to do it faster. Not only do they need to design these products faster, even though they need to be more complex while creating more value to their customers, but they have to do it under tighter regulations. This is especially true for life science companies where one cannot just have a good idea and create a product. A product now has to be characterized, it has to be proven and it has to be validated. These tighter regulations create a higher cost to organizations but the market demands companies to manufacture products cheaper in order to remain competitive. There is huge erosion in the profitability of these markets today. Consequently, things need to be done more efficiently and cost effectively to provide a product that the customer is willing to pay for while maintaining some level of profit margin for the manufacturer. The need for a better way is evident. How does an organization juggle all of these market and regulatory demands? How does an organization know where efficiency improvements can be made? How does an organization visualize the waste that may be in the processes and supply chain? – Enterprise Intelligence is one likely answer to all of these questions.
Look out for the next edition of this Blog Series – An Enterprise Intelligence Strategy