“Essentially, all models are wrong, but some are useful.”
-George E.P. Box
Whether applying G.E.P. Box’s aphorism to scientific theories, your spreadsheet sensitivity analysis, the statistician G.E.P. Box was referring to the limitations of models but can only approximate reality and may not work at boundary or extreme conditions (ie. black swan events).
But the useful models help make sense and are keys to new insights and knowledge. One very useful model to evaluate where your organization is with regards to its use of Business Intelligence & Analytics is to use the DIKW Pyramid.
The DIKW model is a continuum that represents how data provides the foundation of the upper levels. The higher one goes, the higher the value and complexity. The continuum is composed of the following:
1. Data are observed signals, stimuli, symbols, often referred to as ‘facts.’
For example, the temperature of the room where I’m typing this now is at 24˚
2. Information is meaningful, purposeful, relevant data that can answer interrogative questions (eg. who, what, where, how many, when).
For example, the temperature in the room is slightly warmer today, by 0.5 C degree.
3. Knowledge provides framed, contextual information, expert insights and even grounded intuition. Organizations embed knowledge not just in documents and repositories but in routines, processes, practices and norms.
Back to the example, after checking today’s temperature in an ongoing control chart, that data point is an outlier, indicating an assignable root cause (versus normal process variation or true randomness). After some investigation, it indicates that: (1) the air conditioner has been recently serviced and is working well; (2) outside temperature is also significantly hotter than past few days and the same day last few years.
4. Wisdom; as Rowley and Hartley defined this in their book, Organizing Knowledge: An Introduction to Managing Access to Information, wisdom is the ability to increase effectiveness. Wisdom adds value, which requires the mental function that we call judgment. The ethical and aesthetic values that this implies are inherent to the actor and are unique and personal.
Back to the temperature example: the outside temperature is rising significantly and this turns out, after much study by scientists, to be a world-wide trend in the past century. The Earth’s average surface temperature has risen +0.7 °C over a century, and climate model projections indicate to further rise 0.3 to 1.7 °C for their lowest emissions scenario (with stringent mitigation) and 2.6 to 4.8 °C for worst case scenarios. This reminds me to consider presidential candidates that wholeheartedly and concretely support the landmark Climate Accord in Paris.
Does your IT deliver only data? Is your Enterprise on its way to being Intelligent?
Most companies who’ve recently started their own enterprise BI&A want to get the most value and reach the “Holy Grail” or “corporate ideal- a powerful, productive, and exceptionally intelligent organization whose competitive edge comes from its pervasive use of data to drive decisions.”
As the DIKW model makes clear, data is the base of the pyramid – the foundation- of any enterprise Data Warehouse or BI & A service. As the old adage goes, “garbage in, garbage out.” As such, any good BI service should ensure reference or master data and all data sources are accurate, reliable, verified.
But it’s also not enough to have an Analytics organization staffed by quants. To be truly competitive, to be truly an Intelligent Enterprise, an organization should have people at all levels knowing what to do with data and information, processes to retain and grow knowledge and people with the right skills and empowered to drive actions from the insights. BI&A tools should make information easily accessible and easily understood, as well as lend itself to cooperative, collaborative analysis and sharing.
Just as computers were once only given to financial, engineering or scientific staff, computers are now ubiquitous and given to practically all staff, with the requisite tools and training. The same goes for BI&A services- what was once limited to senior management (hence the quaint term ‘management reports’) should be widely disseminated. Embedded systems throughout the supply chain, from the manufacturing line, warehouses, customers’ shelves, provide real-time updates, which minimize the risk of out-of-stock items. Digital retailed like Amazon use past purchase and viewing histories to tailor suggestions every time you go to their site to help you spend even more. This is all done automatically through intelligent, learning algorithms.
In summary, the best-in-class BI&A services enable Intelligent Enterprises. The latter enable, empower intelligent employees, partners and customers, use intelligent systems to fully harness individual, collective, enterprise wisdom and drive a competitive edge in today’s hyper-connected, global marketplace.
Enroll now to learn more about Business Intelligence and Analytics!