Assessing the Strategic Value of Time-Based Data Modeling and Calendar Engineering in Enterprise Power BI Deployments

Abstract:

Enterprises invest heavily in Business Intelligence platforms, yet the temporal layer of the semantic model - the date dimension and the engineering practice that surrounds it - is treated almost universally as a technical detail rather than as an object of strategic investment. This paper asks whether that treatment is warranted. Drawing on the resource-based view and the IT business value literature, it distinguishes time-based data modeling, understood as the structural properties of the temporal layer, from calendar engineering, understood as the practice of designing, governing and maintaining it, and theorises that both contribute to strategic value indirectly, through analytical agility and decision quality, rather than directly. A research model with two antecedents, two mediators, one outcome and one contextual moderator is specified and tested.

Data were collected by cross-sectional survey from 214 enterprise Power BI deployments across six sectors (35.0 % response rate) and analysed by partial least squares structural equation modelling, supplemented by a discounted cash-flow assessment of a representative calendar-engineering programme. The measurement model met the usual thresholds, with composite reliability from 0.85 to 0.92, average variance extracted from 0.63 to 0.70 and a maximum HTMT ratio of 0.78. The structural model explained 57 % of the variance in strategic value, 42 % in analytical agility and 38 % in decision quality. Neither antecedent affected strategic value directly; both operated through the mediators, and calendar engineering exhibited the larger total indirect effect (0.294 against 0.244). Environmental dynamism positively moderated the agility-to-value path. The economic assessment returned a three-year net present value of USD 546,707 on a USD 270,000 initial outlay, an internal rate of return of 103.4 % and a discounted payback of 13.0 months. Subgroup analysis showed the strategic value differential between high- and low-maturity deployments widening from 0.36 to 1.50 scale points as calendar complexity rose, identifying calendar complexity as the principal contingency governing where such investment pays.