Implementation of diversification strategy at Kenya Power And Lighting Company Limited
Bibliographic record
Abstract
Changes in the environment play a great role in the development of an organization‟s overall strategies. Diversification is a corporate strategy that allows the organization to enter lines of business that are different from current operations. Implementation of diversification strategy is one way of helping management of organizations to survive under turbulent environments. This study aimed at illustrating how KPLC had implemented its diversification strategies to strengthen its future survival in a competitive market situation. It also sought to determine the challenges of implementing diversification strategy at Kenya Power and Lighting Company Limited. With the threat of competition, KPLC has prepared itself adequately for any future eventualities. The Company has diversified its business as a way of leveraging the assets and resources and increasing shareholder value. In leveraging on the Supervisory Control and Data Acquisition (SCADA) infrastructure, the Company has installed 1200 km of a 24 pair fibre optic cable on its transmission infrastructure and is utilizing 6 pairs internally with the remaining 18 pairs being made available for lease to licensed telecommunication operators. In future, all new transmission lines are to be built with fibre optic cables. This venture is already earning the company billions of shillings in profits from the leasing of fibre optic infrastructure to telecommunication firms. Through consulting business, the Company has in the recent past entered into international consulting in partnership with Manitoba Hydro International in order to apply its knowledge and experience more widely. Currently KPLC has partnered with MHI to provide managerial services and key executive staff to the electricity companies in Liberia, Rwanda and Afghanistan. The research design used was case study and collection of primary data for the study was done using an interview guide. The data obtained from the personal interviews was analysed qualitatively using content analysis. Findings from the interviewees showed that diversification is very critical to the overall success of KPLC. The interviewees indicated that diversification was a key pillar for the growth of the company and that it had not only increased revenue streams but also dealt with market threats to the organization. Despite of the success in carrying out the study, there were limitations experienced during the overall process. Key among them was the limited time and busy schedules of the interviewees. Not all the interviewees were interviewed as planned due to their busy schedules. Similar studies could be carried out in other government based monopoly utility institutions that have diversified to find out if diversification has been successfully implemented there and come out with a generalised understanding and policies on diversification strategy implementation in such institutions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".