Prioritizing the strategic objectives by integrating the AHP decision model with the strategy map – an applied study

Abstract

Strategic management and the decision-making culture of an organization have vital roles in achieving its desired missions and visions. Decision-makers, especially upper-level managers, play a crucial role in these managerial processes. That is why, organizations should utilize qualitative and quantitative methods to execute these managerial processes more effectively and realistically. These concerns are not only for financial companies but also universities, government units, and non-profit organizations. This study applied a combining methodology that synthesizes a Balanced Scorecard (BSC) for a strategy management framework and an Analytic Hierarchy Process (AHP) for decision-making processes. The methodology focuses on an organization serving the Turkish insurance industry with a dual non-profit and profit-oriented commercial title. The organization functions as a data center of the Turkish insurance industry, aiding in mostly free-of-charge product/service requirements of the industry or government agencies. With these free-of-charge services, the organization aims to support the production level of insurance companies by providing them with processed, improved, and qualified data collected from all the insurance companies in Turkey. Furthermore, the organization is an IT company that can produce its web/web service/website software. The organization can also analyze the fraud organizations in the industry via its fraud prediction models. As the insurance industry is open to fraud cases, it is an important role for the government to protect the industry's security. The organization also uses its software development capability to trade by serving other industry stakeholders who can not deliver software. These trading processes cover the management of all infrastructures and software for some organizations. Additionally, the citizens or other trading organizations; like second-hand vehicle sales companies; can use other paid services of the organization like questioning past insurance activities of a car for sale to get true data. To align with industry demands in the digital age, software systems must ensure consistency and support continuous production, playing a crucial role. Evaluating software development companies is intricate due to the intangible nature of their products. Hence, the organization aims to manage strategic objectives via a strategy map based on the BSC framework and analyze the performance of the map and the priorities of its goals using the AHP model. Through these methodologies, it is believed that the organization can know where the ship is going and lead the steering wheel to the desired route for achieving the final destination. Considering this aim, the Strategy Management Committee thoroughly reviewed existing strategic objectives and crafted a strategy map with the Balanced Scorecard (BSC) framework aligning with the organization's mission and vision. The map prioritized enterprise-level initiatives over learning and growth perspectives, which is why the learning and growth perspective was excluded from the BSC template for this organization. The created BSC model focuses on financial, customer-centric, and enterprise-level perspectives, and under these perspectives, there are strategic focus areas like data management, security, innovation, customer satisfaction, and financial performance where the organization needs to improve its capability. As a second step, The Strategy Management Unit conducted surveys to assess the alignment and impact of strategic goals on the organization's strategy map. The surveys targeted C-suite executives responsible for strategic goals and aimed insights on the impact value of each strategic objective on each focus area. The alignment was conducted after data collection and analysis, highlighting the influence levels of strategic goals on the strategy map. To reveal the importance of perspective and focus areas on the map, the Analytic Hierarchy Process (AHP); has been involved via a group decision conference. Group decision-making with the attendance of selected department managers from the strategy execution committee has progressed. A moderator from the strategy management unit coordinated the decision conference by guiding pairwise comparisons and managing data collection. A structured application involving online platforms and transparent voting conducted pairwise comparisons during the conference. After discussion on the scaling of comparisons was done, the individual voting of scale points and subsequent calculation of geometric averages were conducted to settle the pairwise comparison matrices. Via these judgment matrices, the importance of perspectives and focus areas on the map have been calculated by checking the consistency ratio of each matrix. The consistency ratios of the matrixes were in the acceptable range which is ≤%10. According to the consolidated weights from the hierarchy levels, the service focus area under the customer perspective has the highest value of 0.4647 and it is followed by 0.2037; the data focus area. In the evaluation of the results meeting, upper-level managers of the organizations state that the results are quite acceptable and fit their expectations. As for the perspective weight order, it was customer, enterprise, and financial respectively which order is also suitable for the main functions of the organization in the Turkish insurance industry. As a final step of the applied methodology, the importance levels gathered from the AHP model and the contribution magnitudes of the strategic objectives into the map have been combined with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). This TOPSIS method starts by merging Table 4.6 and Table 4.18 into Table 4.19, demonstrating the weighted normalized rating of strategic objectives. In the same table, the positive-ideal (a^*) and negative-ideal (a^-) solutions can be seen at the bottom. The Euclidean distances; S^* and S^-of each alternative from the ideal solution positive and negative are seen in Table 4.20 respectively. As a last step, the similarity values of the alternatives from the positive ideal solutions have been represented on the right-hand side of the same table with the preference order of the alternative; strategic objectives. According to the final preference order, SO2, SO1, and SO9 are the top three goals for the organization respectively. SO6 and SO3 are very close alternatives that could be considered for the third-level preference. Further insights are hidden in the contributions to the process, service, and data focus areas. Nearly all objectives demonstrate substantial input into these areas, indicating a high level of influence. Consequently, an observation can be made that the organization's strategies predominantly center around customer-centric approaches, with data performing as the primary source of information shaping these strategies. This study uses sensitivity analysis to explore what-if scenarios in the model based on a selected criterion. It is a method used to consider how changing the values of an independent variable; a sub-criterion; can influence a specific dependent variable; alternatives; within a set of assumptions. These assumptions are typically made to understand the reflections of changing the value of a particular criterion in the entire model. Sensitivity analysis is conducted using a reference scale of 0-1 with a defined formula below to explore the influences of specific sub-criteria on the model in this study. The sensitivity analysis has been conducted on the top-weighted focus area which is service under the customer perspective, data, security, and security focus areas respectively. The results show that the building decision model has been affected by the what-if scenarios of the security and innovation focus areas, especially for the top 3 alternatives at the end of the application process. The study is conducted with the analyses of limitations and recommended development areas for future studies. As a last word, it can be said that there is no best methodology for all strategic decision problems, and under these circumcises the researchers or the organizations need to develop their methodologies via trying and searching by considering their specialty in the problem universe.