I am preparing a business case to justify the building of a data warehouse for the University. This has some challenges. While everyone acknowledges that our current BI reports need improved, it is far from obvious how to measure the benefits of improving our BI. Suppose we our student satisfaction score increases in two year's time: how much of that would be due to which specific initiatives, and which of those would result from decisions made with better BI data? It's a tenuous thread of causality.
Nonetheless, if we believe that the decisions made by staff have some impact on outcomes, and that by having better information available to them they will make better decisions, it follows that a successful data warehouse project will have a positive effect. Even if the impact on University income is one tenth of one percent across the board, that would quickly repay the cost of developing and running the service.
Another approach is to look at the costs of not having an integrated source of BI data. This is something we can measure more easily. I've asked some of my colleagues to estimate how much time is spent constructing reports manually, downloading information from multiple systems and putting it together by hand, and they painstakingly revising it when changes are requested. The costs soon mount up.
Without going into specific details on a public forum, each of our academic schools spends a considerable amount of administrator time pulling together this sort of report for the school finance reports, HR reports, and teaching office reports. We have twenty schools, with varying degrees of support from the college offices. Altogether, it is not unreasonable to estimate that the equivalent of 15 full-time equivalent staff (FTE) spend time creating these reports. More time is spent in central support areas as well, easily reaching a total of 20 FTE.
Now, no IT system or process can make everything 100% efficient, certainly not at the first sweep. For this business case, I assume we can make a 50% improvement. That still frees up 10 FTE to do more productive work. As the University is looking to expand, that sort of saving would pay for the data warehouse on its own, even before the advantages of better information kick in.
Nonetheless, if we believe that the decisions made by staff have some impact on outcomes, and that by having better information available to them they will make better decisions, it follows that a successful data warehouse project will have a positive effect. Even if the impact on University income is one tenth of one percent across the board, that would quickly repay the cost of developing and running the service.
Another approach is to look at the costs of not having an integrated source of BI data. This is something we can measure more easily. I've asked some of my colleagues to estimate how much time is spent constructing reports manually, downloading information from multiple systems and putting it together by hand, and they painstakingly revising it when changes are requested. The costs soon mount up.
Without going into specific details on a public forum, each of our academic schools spends a considerable amount of administrator time pulling together this sort of report for the school finance reports, HR reports, and teaching office reports. We have twenty schools, with varying degrees of support from the college offices. Altogether, it is not unreasonable to estimate that the equivalent of 15 full-time equivalent staff (FTE) spend time creating these reports. More time is spent in central support areas as well, easily reaching a total of 20 FTE.
Now, no IT system or process can make everything 100% efficient, certainly not at the first sweep. For this business case, I assume we can make a 50% improvement. That still frees up 10 FTE to do more productive work. As the University is looking to expand, that sort of saving would pay for the data warehouse on its own, even before the advantages of better information kick in.
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