Business Intelligence, Sales Forecasting and Knowledge Management

Introduction

Business intelligence may be defined as the process of improving the way an organization makes its decisions. This is achieved by the systematic process of examining, acquiring, and managing external and internal information and knowledge.

Knowledge management can be defined as the process of making intangible assets within an organization valuable. This is achieved by the process of controlling knowledge that may be either internal or external within the organization. Therefore knowledge management can be defined as the process of manipulating knowledge. This can be through acquiring it, analyzing it, sharing it, distributing it, identifying it, and creating it.. (Kahn, 2000)

Sales forecasting is the process of incorporating all the key aspects in sales to enable a prediction of future sales events. This means that there can be business activities carried out continuously on a monthly basis, customer history and leads in sales. All these factors need to be collected analyzed and used in the process of forecasting. This can only be achieved by the integration of business intelligence. Therefore business intelligence facilitates sales forecasting and efforts made towards the achievement of the concept. (Mentzer, 1999)

Business intelligence is becoming an increasingly common strategy in organizations lately. This means that companies are integrating it into all aspects and not just specific areas. These companies are also dealing with planning and skills necessary to implement business intelligence. However, there are a number of issues that have to be incorporated during the process of implementing business intelligence. (Kahn, 2000) These include the process itself, cultural aspects of the organization, and the people that will be involved in the process. In line with this were some predictions made by Gartner Group that there would be an increase in revenue generated from licensing software to be used for implementing business intelligence.

Factors that distinguish between business intelligence and knowledge management

Knowledge management facilitates business intelligence

Among the many aspects of knowledge management, is gaining experiences from past failures and successes. There are Lessons- Learned Information Systems that are used by NASA. These systems are used to distribute, acquire and examine lessons to members of the organization such that they can be more successful in their future endeavors. Knowledge management is customized to fit a specific user. What users normally do is that they give information regarding their profile, and then when lessons that fit that profile are available, they are sent through email to the user. Therefore the user generates an interest in the lessons because they apply directly to him/her. (Hansen, 1999)

Differences in applications of business intelligence and knowledge management

Business intelligence is defined around data warehousing where data warehousing is the collection of data that is relevant to the organization. This data is then arranged in a storage format that can be practical to the organization and can be applied in the Company’s decision-making process. This business data can be collected from a number of avenues. These avenues are called operational data stores. After the information is obtained from the data sources, it is then sent to data marts. (Mentzer, 1999)

It is common to find that some of the data collected may not be of value to the organization so these portions of data are eliminated. This is what is called data cleansing. Within these data marts, data is modeled into multidimensional forms. This will be such that there are ways that the system can be drilled down. Users can be able to query aspects of the data mart through tools available commercially like Cognos and Brio. All in all, these warehouses vary in size; there are large ones that can hold data reaching the terabyte level. Small-sized ones hold data that lies within the gigabyte range.

However, knowledge management is associated with organizational behavior, management of content, collaboration, and various technologies. This means that knowledge management is normally applied to cases where there is unstructured information like text documents. These documents are essential to the business because there is a lot of knowledge that can be obtained from these unstructured sources.

These sources signify a future in the world of business data because they allow a deeper understanding of certain events that are characteristic of a particular business. These applications are also relevant to the organization with regard to competition, the market, and the customer. There are also other areas where knowledge management has its relevance. These are finance, life sciences, manufacturing, and consumer goods. (Mentzer, 1999)

Differences between business intelligence and sales forecasting

Managing business intelligence facilities sales forecasting

Before one can differentiate between the two concepts, it is important to define some terms that will be used in the process of distinguishing the two. Data can be considered as numbers that have not been analyzed, information can be defined as data that has been organized, analyzed, and summarized while knowledge may be defined as the in-depth analysis and correlation of past experiences to establish a trend that will be used in making decisions. (Hansen, 1999)

Therefore sales forecasting can only be achieved when knowledge is incorporated to come up with trends that will facilitate a decision regarding the way sales will behave in the future. But there is a distinctive difference that arises when differentiating between knowledge manipulation and sales forecasting. Forecasting also involves an exchange of data between people and various sections of the organization.

Distinctive features in sales forecasting and business intelligence

While business intelligence may be applied to the entire organization, sales forecasting is normally facilitated by the exchange of intelligence between various people or individuals. Most of the exchanges are normally done through the use of data and information. However, the percentages differ. Most of the sales forecasts that have been done in the past have focused on data that contributed to 52% of what had been exchanged. This is in contrast to 42% for information that was exchanged. (Cody, 2002)

Sales forecasting is normally implemented differently as compared to business intelligence. Normally, business intelligence will be done by data warehousing and analysis but sales forecasting can be transmitted by word of mouth. It is also done through meetings where members can exchange ideas through data and information. This, therefore, brings a major difference between Business Intelligence and Sale Forecasting. The former concept normally involves analytical techniques as a strategy to implement that change within an organization. But the latter concept may not work out when such a similar strategy is employed, instead, there should be the use of a personalization strategy to ensure the success of the method.

However, if a company would like to incorporate the use of data, then they can use another strategy for sales forecasting. This is the codification strategy. Here, the database can be used since there is a way to facilitate understanding of the data present and this will ease the exchange of information between parties. (Kahn, 2000)

Satisfaction can only be attained in sales forecasting when there is the proper use of knowledge. Research has verified that the latter statement is true for most Companies. Therefore it is not simply business intelligence that must be incorporated in sales forecasting but it must also include knowledge management. If knowledge is distributed efficiently throughout the organization and is also integrated, then an organization will be able to function more efficiently. (Cody, 2002)

Lastly, sales forecasting can only reach its potential if there is the incorporation of business intelligence in the former process. Previously, companies have been considering sales forecasts to fall under the techniques section yet this is not necessarily the case, it is indeed a process. Besides this, business intelligence incorporates data, knowledge, and information. These are all elements that are useful in sales forecasting and can therefore be applied in the process of sales forecasting.

Conclusion

Knowledge management is different from business intelligence because knowledge management is simply used to facilitate business intelligence. For example, by distributing knowledge to users who need it, the organization will improve its decision-making ability and hence improve business intelligence. (Cody, 2002) Another major difference between the two concepts is the fact that their applications within organizations are usually distinct and different. Knowledge management is usually associated with organizational behavior and unstructured information, however business intelligence is associated with data warehousing.

There are also some distinct differences between business intelligence and sales forecasting. First of all sales forecasting is achieved by incorporating business intelligence. (Mentzer, 1999) Besides this, the strategy used to implement business intelligence is different from sales forecasting. In business intelligence, organizations use analytical strategies while in sales forecasting, organizations use person to person strategies.

Reference

Hansen, M. et al (1999): What’s Your Strategy for Managing Knowledge; Harvard Business Review, pp. 106-116.

Kahn, B. (2000): Benchmarking New Product Forecasting Practices; Institute Of Business Forecasting Research Report.

Mentzer, J. et al (1999): Benchmarking Sales Forecasting Management; Business Horizons, pp. 48-56.

Cody, W. et al (2002): The integration of business intelligence and knowledge management. IBM systems journal, vol. 41, No. 4. Web.