| Introduction | | | | forecasting |
| Business intelligence may be defined as the | | | | Before one can differentiate between the two |
| process of improving the way an organization | | | | concepts, it is important to define some terms |
| makes its decisions. This is achieved by the | | | | that will be used in the process of distinguishing |
| systematic process of examining, acquiring and | | | | the two. Data can be considered as numbers that |
| managing external and internal information and | | | | have not been analyzed, information can be |
| knowledge. | | | | defined as data that has been organized, analyzed |
| Knowledge management can be defined as the | | | | and summarized while knowledge may be defined |
| process of making intangible assets within an | | | | as the in-depth analysis and correlation of past |
| organization valuable. This is achieved by the | | | | experiences to establish a trend that will be used |
| process of controlling knowledge that may be | | | | in making decisions. (Hansen, 1999) |
| either internal or external within the organization. | | | | Therefore sales forecasting can only be achieved |
| Therefore knowledge management can be | | | | when knowledge is incorporated to come up with |
| defined as the process of manipulating knowledge. | | | | trends that will facilitate a decision regarding the |
| This can be through acquiring it, analyzing it, | | | | way sales will behave in the future. But there is a |
| sharing it, distributing it, identifying it and creating it. | | | | distinctive difference that arises when |
| . (Kahn, 2000) | | | | differentiating between knowledge manipulation |
| Sales forecasting is the process of incorporating all | | | | and sales forecasting. Forecasting also involves an |
| the key aspects in sales to enable a prediction of | | | | exchange of data between people and various |
| future sales events. This means that there can be | | | | sections of the organization. |
| business activities carried out continuously on a | | | | Distinctive features in sales forecasting and |
| monthly basis, customer history and leads in sales. | | | | business intelligence |
| All these factors need to be collected analyzed | | | | While business intelligence may be applied to the |
| and used in the process of forecasting. This can | | | | entire organization, sales forecasting is normally |
| only be achieved by the integration of business | | | | facilitated by the exchange of intelligence between |
| intelligence. Therefore business intelligence | | | | various person or individuals. Most of the |
| facilitates sales forecasting and efforts made | | | | exchanges are normally done through the use of |
| towards achievement of the concept. (Mentzer, | | | | data and information. However, the percentages |
| 1999) | | | | differ. Most of the sales forecasts that have been |
| Business intelligence is becoming an increasingly | | | | done in the past have focused on data which |
| common strategy in organizations lately. This | | | | contributed to 52% of what had been exchanged. |
| means that Companies are integrating it into all | | | | This is in contrast to 42% for information that |
| aspects and not just specific areas. These | | | | was exchanged. (Cody, 2002) |
| companies are also dealing with planning and skills | | | | Sales forecasting is normally implemented |
| necessary to implement business intelligence. | | | | differently as compared to business intelligence. |
| However, there are a number of issues that have | | | | Normally, business intelligence will be done by data |
| to be incorporated during the process of | | | | warehousing and analysis but sales forecasting can |
| implementing business intelligence. (Kahn, 2000) | | | | be transmitted by word of mouth. It is also done |
| These include the process itself, cultural aspects | | | | through meetings where members can exchange |
| of the organization and the people that will be | | | | ideas through data and information. This therefore |
| involved in the process. In line with this were | | | | brings a major difference between Business |
| some predictions made by Gartner Group that | | | | Intelligence and Sale Forecasting. The former |
| there would be an increase in revenue generated | | | | concept normally involves analytical techniques as |
| from licensing software to be used for | | | | a strategy to implement that change within an |
| implementing business intelligence. | | | | organization. But the latter concept may not work |
| Factors that distinguish between business | | | | out when such a similar strategy is employed, |
| intelligence and knowledge management | | | | instead, there should be use of a personalization |
| Knowledge management facilitates business | | | | strategy to ensure success of the method. |
| intelligence | | | | However, if a company would like to incorporate |
| Among the many aspects of knowledge | | | | the use of data, then they can use another |
| management, is gaining experiences from past | | | | strategy for sales forecasting. This is the |
| failures and successes. There are Lessons- | | | | codification strategy. Here, the database can be |
| Learned Information Systems that are used by | | | | used since there is a way to facilitate |
| NASA. These systems are used to distribute, | | | | understanding of the data present and this will |
| acquire and examine lessons to members of the | | | | ease exchange of information between parties. |
| organization such that they can be more | | | | (Kahn, 2000) |
| successful in their future endeavors. Knowledge | | | | Satisfaction can only be attained in sales |
| management is customized to fit a specific user. | | | | forecasting when there is proper use of |
| What users normally do is that they give | | | | knowledge. Research has verified that the latter |
| information regarding their profile, and then when | | | | statement is true for most Companies. Therefore |
| lessons that fit that profile are available, they are | | | | it is not simply business intelligence that must be |
| sent through email to the user. Therefore the | | | | incorporated in sales forecasting but it must also |
| user generates an interest in the lessons because | | | | include knowledge management. If knowledge is |
| they apply directly to him/her. (Hansen, 1999) | | | | distributed efficiently throughput the organization |
| Differences in applications of business intelligence | | | | and is also integrated, then an organization will be |
| and knowledge management | | | | able to function more efficiently. (Cody, 2002) |
| Business intelligence is defined around data | | | | Lastly, sales forecasting can only reach its |
| warehousing where data warehousing is the | | | | potential if there is incorporation of business |
| collection of data that is relevant to the | | | | intelligence in the former process. Previously, |
| organization. This data is then arranged in storage | | | | companies have been considering sales forecasts |
| format that can be practical to the organization | | | | to fall under the techniques section yet this is not |
| and can be applied in the Company's decision | | | | necessarily the case, it is indeed a process. |
| making process. This business data can be | | | | Besides this, business intelligence incorporates |
| collected from a number of avenues. These | | | | data, knowledge and information. These are all |
| avenues are called operational data stores. After | | | | elements that are useful in sales forecasting and |
| the information is obtained from the data sources, | | | | can therefore be applied in the process of sales |
| it is then sent to data marts. (Mentzer, 1999) | | | | forecasting. |
| It is common to find that some of the data | | | | Conclusion |
| collected may not be of value to the organization | | | | Knowledge management is different from |
| so these portions of data are eliminated. This is | | | | business intelligence because knowledge |
| what is called data cleansing. Within these data | | | | management is simply used to facilitate business |
| marts, data is modeled into multidimensional | | | | intelligence. For example by distributing knowledge |
| forms. This will be such that there are ways that | | | | to users who need it, the organization will improve |
| the system can be drilled down. Users can be able | | | | its decision making ability and hence improve |
| to query aspects of the data mart through tools | | | | business intelligence. (Cody, 2002) Another major |
| available commercially like Cognos and Brio. All in | | | | difference between the two concepts is the fact |
| all, these warehouses vary in size; there are large | | | | that their applications within organizations are |
| ones that can hold data reaching the terabyte | | | | usually distinct and different. Knowledge |
| level. Small sized ones hold data that lies within the | | | | management is usually associated with |
| gigabyte range. | | | | organizational behavior and unstructured |
| However, knowledge management is associated | | | | information, however business intelligence is |
| with organizational behavior, management of | | | | associated with data warehousing. |
| content, collaboration and various technologies. | | | | There are also some distinct differences between |
| This means that knowledge management is | | | | business intelligence and sales forecasting. First of |
| normally applied to cases where there is | | | | all sales forecasting is achieved by incorporating |
| unstructured information like text documents. | | | | business intelligence. (Mentzer, 1999) Besides this, |
| These documents are essential to the business | | | | the strategy used to implement business |
| because there is a lot of knowledge that can be | | | | intelligence is different from sales forecasting. In |
| obtained from these unstructured sources. These | | | | business intelligence, organizations use analytical |
| sources signify a future in the world of business | | | | strategies while in sales forecasting, organization |
| data because they allow a deeper understanding | | | | use person to person strategies. |
| of certain events that are characteristic of a | | | | Reference |
| particular business. These applications are also | | | | Hansen, M. et al (1999): What's Your Strategy for |
| relevant to the organization with regards to | | | | Managing Knowledge; Harvard Business Review, |
| competition, market and the customer. There are | | | | March-April, pp. 106-116 |
| also other areas where knowledge management | | | | Kahn, B. (2000): Benchmarking New Product |
| has its relevance. These are finance, life sciences, | | | | Forecasting Practices; Institute |
| manufacturing and consumer goods. (Mentzer, | | | | Of Business Forecasting Research Report |
| 1999) | | | | Mentzer, J. et al (1999): Benchmarking Sales |
| Differences between business intelligence and | | | | Forecasting Management; Business |
| sales forecasting | | | | Horizons, May-June, pp. 48-56. |
| Managing business intelligence facilities sales | | | | |