Fast and accurate decision-making has become very important in today’s business world. It can make the difference between a successful enterprise and one that is heading toward failure. This may be an extreme case but the latest financial crisis demonstrated that in time decision-making can make the “life to death” difference for a business. Nowadays, business decisions are taken on unprecedented scales in history. In today’s market, multi-million business decisions are common. It has become crucial to make faster decisions than the competition. Many times several companies are competing for the same markets and products.
So, making faster decisions can give a head start and enables you to gain greater shares of the market. But there is an important point to be made here. The decisions must not be only fast. When making these decisions it is imperative that businesses understand, or gain as much understanding of, the decision in question to maximize the firm’s profitability. To gain this understanding, to have a head start in front of the competition, companies need to collect and examine a huge quantity of data.
The secret is turning these “mountains of data” into a real competitive advantage. Seeing that humans are “too slow” in processing this data these companies are turning more and more to technology. No doubt that today’s machines are way faster in processing information than any human being. This helps cut the labor costs and increases the speed of collection and procession of the data. Due to these necessities, there are several areas of study that are designed to help businesses in their decision-making process. Business intelligence, sales forecasting, and knowledge management are some of these. And the simple question that one might make immediately is: what do these terms stand for? It would be of interest to explain them and see what, if anything, is different between them. First, we have to understand what business intelligence is.
Business intelligence has more than one definition. One is that:
“BI (business intelligence) is an interactive process of analyzing and exploring structured, domain-specific information (often stored in a data warehouse) to discern trends or patterns, thereby deriving insights and drawing conclusions. The BI process includes communicating findings and effecting change. BI domains include customers, products, services or competitors”.
Another definition is:
“BI is a broad category of technologies that allow for gathering, storing, accessing and analyzing data to help business users make better decisions”.
And yet a third that:
“BI is a system or systems that provide directed background data and reporting tools to support and improve the decision-making process”.
As we can see there are many related definitions of business intelligence. According to these definitions, business intelligence is the sum of all the data, information, and knowledge that a company has. Its focus is on the processing of data. By processing data business intelligence can then be used for supporting decisions, forecasting future events, or discovering trends within a set of information. But where does this information, this mountain of data, come from? It is no more than the raw numbers generated from the everyday activities that every business has. This is information that connects the supplier with the customer, consumer, through the business company.
The main point is to analyze the performance of the company, to watch the status of the supply and that of the demand, and to try and find trends that can help predict future behaviors. This information is crucial especially to managers that take it and determine the strategies and tactics that their company should implement to be ahead of the competition. This is why technology is so needed in processing fast information. This is why business intelligence is essential if you want to launch new products or services in the market, change or modify the ones that you already have, understand what consumers want and suppliers can give. In the words of a specialist like Mike Schroeck, managing partner of the analytics practice at PricewaterhouseCoopers, on business intelligence:
“Analytics can help companies identify areas to pursue, which customers to target. And most important, it can show them the impact or payback from introducing a new product or service in a manner timely enough that they can refine and adjust their strategies.” (Kirkpatrick, 2002: p.2).
Let see now what knowledge management is and its difference with business intelligence.
“Knowledge management is a system or framework for managing the organizational processes that create, store and distribute knowledge, as defined by its collective data, information, and body of experience”.
Or, another one that:
“Knowledge management is a business process that formalizes management and leverage of a firm’s intellectual assets. KM is an enterprise discipline that promotes a collaborative and integrative approach to the creation, capture, organization, access, and use of information assets, including the tacit, uncaptured knowledge of people.”.
Even knowledge management is a systematic business optimization strategy that stores, organizes, processes, and communicates information that is essential to the company to improve company performance. And to this point, it is similar to business intelligence. What is different is that knowledge management has in its focus even the improvement of employee’s performance. It has a direct preoccupation with its employee status. It recognizes that company success is not only in analyzing data from the suppliers and consumers but also the “emotional and motivation” status of its employees. This is something that business intelligence does not take into much consideration. These are similar types of analytics, very close ones, but I think one major difference is the “human employee factor” that knowledge management takes into serious account. This factor gives way to the creation of new knowledge or the dispersion of knowledge. Naggy has proposed an interesting table presentation of the comparison and contrast of the activities of business intelligence and knowledge management.
|Knowledge Management||Business Intelligence|
|1. Capture data||1. Capture data|
|2. Organize data||2. Organize data|
|3. Analyze data||3. Analyze data|
|4. Aggregate data||4. Aggregate data|
|5. Apply data||5. Apply data|
|6. Create new knowledge||6. No equivalent action!!!!!!|
|7. Knowledge dispersion||7. No equivalent action!!!!!!|
Let pass to the next concept discussed here. Sales forecasting is the term used to describe “the process of estimating what your business’s sales are going to be in the future” (Ward, 2008, p. 1). If you are a new business it is hard for you to do this because you have no historical data to analyze. What you can do is conduct research into the target market, competitors, and operating area to estimate sales and make predictions on your sales. This means sales forecasting is similar to business intelligence. I would say that it is part of it since the latter does forecasting over the company’s sales activity. But it also analyses data for managers to have the ability to create new products or services. That gives managers the “feeling” over the market and how is it going to react in the future.
The last concept is that of common sense in business. There is no specified definition of what common sense in business means. This is strange if you think that many successful businesses including, but not only, Warren Buffet, Richard Branson, and Bill Gates contribute their success to common sense. It is a sort of “talent” or “intuitive knowledge”. It is very difficult to learn it in a business school. People are either born with it or gain it slowly over many years of experience. While business intelligence, sales forecasting, and knowledge management are all very important to businesses, they can never replace common sense. The first three let you understand very well the past and the present of your business. On that basis, a manager tries to make predictions over the future of the company and what should be done to adapt the best possible ways to make that future brilliant. But the problem is that with predictions you are never sure that you have made it right. The way you collect information, how you structure it, which is more valuable and which less, and how you turn that information into positive knowledge for the business, can be made in different ways. It is here that common sense enters the play.
It acts as a kind of “methodology” that enables managers to do the above-mentioned processes in the best ways possible. Especially at the step where you need to turn information into knowledge, having analysts with a great deal of common sense will prove invaluable (Cody et al., 2002: p.14). By saying that I am stating that common sense and business intelligence difference is that the former acts as a kind of “methodology” for the latter. Common sense is the method by which you use the tools of business intelligence. In this regard, it can also be seen as part of business intelligence. And in fact, it is. Having managers with little common sense in business will make it very difficult for the company to have good market results. These managers will not be able to properly use the business intelligence tools to make their business more and more successful.
Kahn, K.B. & Adams, M.E. (2001). Sales forecasting as a knowledge management process. The Journal of Business Forecasting.
Nagy, D. (n.d.). Business Intelligence and Knowledge Management Differences.
Cody, W. F., J. T. Kreulen, V. Krishna & W. S. Spangler (2002) The integration of business intelligence and knowledge management. IBM SYSTEMS JOURNAL, VOL 41, NO 4. Web.
Kirkpatrick, T. (2002) Analysis: Business Intelligence. CIOInsight 2002-3-18.