Business Intelligence In Kraft Foods: Tools, Techniques, And Value For Customers

Tools and Techniques Used by the Business in Supporting Business Intelligence

Kraft Foods is a global powerhouse in the production of confectioneries, quick meals, and snacks that recognize the use of business intelligence in its production and planning, logistics, and operational management. Kraft Foods uses tools and techniques that increase its performance due to the firm intelligence formula it has chosen.

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Previously, the company performed below its expectations until the adoption of the SAP’s products in business strategy that has increased its performance. SAP is a global software company and one of the largest vendors of the information technology application software and other enterprise applications (Forsgren and Sabherwal 2015). The system allows the company to run its business processes ranging from the sales, accounting, production, and the human resource departments.

Kraft Foods introduced the master data management plan which simplifies and harmonized its business globally thereby enabling a strategic enterprise information handling. The firm grew by acquiring and assessing its master data plan and aligned them towards its business strategies. However, the master of the data plan program played a key role in providing a data plan for the finished products, vendors, customers, materials, and location information (Elbashir, Collier, Sutton, Davern and Leech 2013). The program has been instrumental in reducing product portfolio complexity, increased accuracy, and a reduction in the inventory challenges.

Besides, the use of the software has guaranteed the reliable obtaining of sales views from customers, enhancing product evaluation, and increasing reliability during the measurement and ranking of the business partners (George Kumar and Kumar 2015). Besides, the ability of the software to project the future operations gives the firm the power to respond to business opportunities and address their challenges before they affect the firm’s production. The reality assists the firm in increasing the information flow and correlation between departments enabling financial transparency, data entry, and legal controls (George, Kumar, and Kumar 2015). At the same time, the software assists in obtaining a proper utilization of the resources concerning machines and human resources planning within the organization.

The measure by the firm drives real benefits through the provision of auxiliary sales information as well as an analysis and projection of the demand and supply scenario. The attribute assists the company in projecting the market needs and thus produce matching numbers of product for its global market (Isik, Jones and Sidorova 2013). Besides, the firm has experienced an increased future projection in its sales, and the fact assists it in aligning its products with the trends in the market. Consequently, the move has increased the competitive nature of the business and therefore given it an upper hand in business growth.

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The company uses a well-integrated system in offering its transport solutions to the customers. The firm has experienced changes in its operation through the implementation of Oracle Fusion Transportation Intelligence which has a large supply chain of more than 900,000 annual shipments (Laursen and Thorlund, 2016). The application increased the distribution capability of the firm while utilizing its ERP business intelligence solution for transport management.

Further, it is evident that the company has increased its supply chain management given the adequate delivery of its products in the market which remains visible due to an integrated supply chain scenario. At the same time, the firm has achieved a better order fulfillment as it can match the order according to its production in the market. In this case, the company has benefited widely from the SAP procedures that have improved the time taken to deliver goods and services. On the other hand, the clients receiving the products have responded positively, and the fact has promoted the likelihood of the firm to retain and attract a considerable number of people.

Improvements Observed in the Company in Comparison to Others

On the other hand, the firm established a base structure that entailed the volume, cost, and service calculations which have provided an upfront development within the organization for transport solution. The upfront enables the firm to develop a broad foundation for other development processes. The provision of data guarantees information flow within and outside of the organization thus improving the communication aspect of the firm. Currently, most of the back office information are technically enabled leading to faster delivery and processing of information. The information sharing between departments remains at all time high thereby increasing the production capability of the firm. Consequently, the firm has benefitted from the SAP technology as evidenced by the way it had transformed its production system.      

Business intelligence improves the operational processes of organizations. In this respect, it affects the customers by according them timely delivery of orders that meet their demands. Customers can place orders and have them produced in an elegant manner and delivered promptly through the firm’s supply chain. At the same time, the firm enjoys an information technology enabled accounting system that allows a timely purchase and payment for the orders thus reducing the time spent by individuals in making a purchase. The clients benefit from improved products given the introduction of information technology in the firm’s manufacturing process. Business customers who are interested in becoming partners in the firm will have a timely report that allows them to review the business development and make decisions on making subsequent purchases (Sauter 2014).

On the other hand, the firm benefits a lot from the business intelligence system. First, the enterprise resource planning enables the firm to develop and use software that improves the performance of the organization. First, it drives value to the company by allowing it achieve its vision of providing real products in real time to the clients. In return, the firm earns profits thereby leading to increased revenue. As opposed to other firms not utilizing the model, the company remains competitive by outshining its competitors using the traditional models.

 Consequently, the firm can expand its services across the globe. Secondly, the business derives value from the proper transport system from a firm that is internationally recognized and its several volumes of orders handled at a time (Selene Xia and Gong 2014). The fact drives value for the business regarding the ability to expand to other locations in the world where it had no such businesses previously. Besides, the timely delivery of products and in the desired volume increases the loyalty standards of the clients who in turn introduce others to the business.

 Therefore, the firm gets value by increased revenue through the use of the technology that guarantees a faster processing of orders (Trieu 2017). Moreover, the company gets value experienced in the reduced operational costs experienced in the earlier situation. The firm can carry a large number of tasks that almost double the last production which not only increases its revenue but also improve the rate of which employees enjoy their work through complexity reduction. Furthermore, the firm remains an example in the market offering real-time solution to the needs of the market. The timely and demand meeting  deliveries give the company a strong brand name that the organization counts on in engaging in more business practices. In the long run, the firm is set to benefit from the situation and score higher.  

Business Intelligence and the Value it Drive in Business

The organization is a critical factor towards the success of organizations implementation of business intelligence. Kraft Foods has a well-organized management that supports the implementation both financially and regarding resource allocation. The strength gives the implementation team the desire and motivation to implement the scope towards success. Besides, the firm has aligned the business intelligence towards its organizational factors thereby working coherently within the system (Moro, Cortez and Rita 2014). At the same time, the firm frequently identifies its key performance indicators and reviews them towards business success.

 In this case, the company guarantees a proper working by enhancing the indicators with strength and rectifying on those that pose adverse effects to the organization.

The firm is willing to employ outside experts on the part-time basis to conduct training activities on the employees to increase their efficiency and mastery of knowledge. Besides, it employs permanent staff who works wholeheartedly towards progress. On the other hand, the business improves its recruitment and training center where it takes in workers that match the necessary skills required for improved production in line with the technology used (Calof, Richards and Smith, 2015).

Further, the firm has an adequate process management which aligns the right skills with the desired process thus initiating change. The company involves the technical and business personnel in the needed change thus providing a wholesome transformation in the way the business is managed. Apart from the internal staff, the firm embraces the services of the external experts in the change management which increases the probability of meeting the demands of change and rectifying the current mistakes towards success (Ryan 2014).

Lastly, the firm embraces technology and uses it in almost all the processes in the organization thus increasing the efficiency in production (Bimonte, Schneider and Boussaid, 2016). The firm uses data quality in business content which enhances the performance of the organization. Furthermore, the data centers remain protected using the latest technology to guarantee security and technical support in case of failure. Therefore, the willingness of the organization to fully incorporate the business intelligence model ensures success for the firm.

References

Bimonte, S., Schneider, M. and Boussaid, O., 2016. Business Intelligence Indicators: Types, Models and Implementation. International Journal of Data Warehousing and Mining (IJDWM), 12(4), pp.75-98.

Calof, J., Richards, G. and Smith, J., 2015. Foresight, competitive intelligence and business analytics—tools for making industrial programmes more efficient. Foresight-Russia, 9(1), pp.68-81.

Elbashir, M.Z., Collier, P.A., Sutton, S.G., Davern, M.J. and Leech, S.A., 2013. Enhancing the business value of business intelligence: The role of shared knowledge and assimilation. Journal of Information Systems, 27(2), pp.87-105.

Forsgren, N. and Sabherwal, R., 2015. Business Intelligence System Use as Levers of Control and Organizational Capabilities: Effects on Internal and Competitive Benefits.

George, J., Kumar, V. and Kumar, S., 2015. Data Warehouse Design Considerations for a Healthcare Business Intelligence System. In World Congress on Engineering.

Isik, Ö., Jones, M.C. and Sidorova, A., 2013. Business intelligence success: The roles of BI capabilities and decision environments. Information & Management, 50(1), pp.13-23.

Laursen, G.H. and Thorlund, J., 2016. Business analytics for managers: Taking business intelligence beyond reporting. John Wiley & Sons.

Moro, S., Cortez, P. and Rita, P., 2014. A data-driven approach to predict the success of bank telemarketing. Decision Support Systems, 62, pp.22-31.

Ryan, L., 2014. A New Era of Business Intelligence Education: Preparing Ethical Next-Generation Technology Leaders. In Strategies for Teaching Leadership. CreateSpace.

Sauter, V.L., 2014. Decision support systems for business intelligence. John Wiley & Sons.

Selene Xia, B. and Gong, P., 2014. Review of business intelligence through data analysis. Benchmarking: An International Journal, 21(2), pp.300-311.

Trieu, V.H., 2017. Getting value from Business Intelligence systems: A review and research agenda. Decision Support Systems, 93, pp.111-124.

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