Digital Transformation Payday

CHAPTER 14Predictor Financials: Your P&L and Balance Sheet Context Indicate Your Ability to Achieve Your Payday

Industry groups are only one possible angle to cluster firms based on externally observable characteristics. Much more obvious to use are the financial key performance indicators (KPIs) of our analyzed firms. This should further enable us to better understand the context these firms are operating in. Fortunately, based on the advancements of econometric models, we can build on our orthoforest‐based causal estimate model (Chapter 10) to run detailed elasticity analysis for DIGITALPROXY on logMARKETCAP. I again spare you the technical details here. (See some more explanation in Appendix F.) In simple words, this helps to answer the question about how the correlation impact (and indicative causality) of digital transformation efforts changed in our dataset depending on different observable financial KPIs and their characteristics (e.g., negative versus around zero versus high net income).

Table 14.1 shows the results, based on logMARKETCAP elasticity and a flag for the risk (*** = lowest risk) that the prediction is not as precise as one would wish (in terms of wideness of confidence interval), for all key operational KPIs. Given that such analysis is still in early stages, this should be further expanded in future research and will have to be carefully interpreted.

In any case, you can clearly see across all major variables, however, that firm context heavily influenced ...