Building a data-driven culture in Business Schools

6. Dec 2021 | 6th edition: Focus on the MENA region, Academ & Qace Up Knowledge Bar, Articles

Data is the lifeblood of every Higher Education Institution (HEI) in nowadays dynamic environments. There is much resistance from business schools to adopt a data-driven culture despite that much empirical research suggests that data-driven organizations outperform their peers. During the last two years, business schools have increasingly been experimenting with their online learning experience and discovering the benefits of data adoption to improve decision-making processes.

By Hatem Masri (LinkedIn), Gagan Kukreja (LinkedIn) and Hessa Al-Fadhel (LinkedIn)
College of Business Administration, University of Bahrain

Business schools engaged in an AACSB accreditation are using data to meet AACSB standards, such as faculty qualification ratios and to assess the KPIs in their strategic plan. These schools demonstrated a good alignment between strategic, tactical, and operational levels in the school/University. This alignment offered a chance for everyone to move together in the same direction.

“If everyone is moving forward together, then success takes care of itself.” (Henry Ford)

Several business schools have benefited from this alignment to create dashboards to monitor long-term strategic success and mid-term faculty and program performance. For business schools, the performance of faculty was guided by academic and professional outcomes, while programs were assessed through benchmarking and assurance of learning practices. Business schools can benefit from internal and external data in order to achieve better agility, sourcing, and process efficiency. External data can be found for example through the AACSB’s DataDirect, a hub for business education data. Internal data for a business school is information, statistics, and trends that the school collects from its operations. One of the internal data sources at the University of Bahrain is ACADEM by RimaOne. The usage of ACADEM is not limited to generate the required tables for an AACSB accreditation visit. ACADEM is also leveraged to manage and optimize faculty talents.

A faculty’s main activities are teaching, research, and engagement with the community and other stakeholders. Teaching can have a direct impact on local and regional level development when courses reflect the needs of the labour market. While in research, faculty contribute to innovations through reflecting local, regional and global needs in research topics, along with signing research agreements with other players in the community. As for engagement, collaborating with both private and public sectors is vital to maintain the networks of learning and innovation. The performance of faculty members is a combination of their scientific capabilities with the interpersonal characteristics in a way that accumulate experiences and deliver an outstanding performance.

The challenge that is being faced by many business schools is maintaining qualified faculty members, while having limited resources, especially when they are competing with international organizations for hiring the best researchers. Most of the accreditation agencies require having appropriate faculty with suitable academic and professional qualifications to receive the accreditation. AACSB standards for example require business schools to ensure having the right proportion of academically qualified instructors. EQUIS standards emphasize on having faculty members with suitable profiles of qualification and (international) experience. At the same time, each higher education programme or course may have their very own requirements for the instructors delivering said programme or course. It’s the challenge for any institution to match their own requirements with those of the accreditation agencies resulting in unified guidelines in terms of required skills and qualifications needed to deliver a given programme or course.

Recently, Al-Abbasi and Masri [1] benefited from data in ACADEM to develop a faculty talents optimization framework using a perspective analytics (ELECTRE IV) that offers faculty an overall overview of their performance and targets set in order to align with the business school goals and KPIs.

Unfortunately, not all business schools have started using the power of predictive and perspective analytics for decision making. Most of the business schools are using descriptive data for reporting purposes in terms of rankings and accreditations.

“When the number is known the surprise becomes void”

A data-driven culture in business schools should result in a more effective strategy, thoughtful and fast decision-making and a culture of trust and commitment.

If in your business school, decision-making takes too long, you have too many meetings, you are overloaded with emails, the departments are silos, you have an unclear responsibility, there is a lack of empowerment at lower levels, communication is selective, then the right solution is to build a data-driven culture in the school.

In the College of Business Administration at the University of Bahrain, we valued the importance of data in vehiculating the continuous improvement process and quality assurance. The College has engaged with ACADEM and other big data partners to exploit data to provide better educational experiences, leading to enhanced retention and achievements.


1 Al-Abbasi, S. and Masri, H. (2020), “Optimizing faculty talents through identifying entrepreneurial champions: an ELECTRE IV approach”, Management Decision, Vol. 58 No. 11, pp. 2527-2541.


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