As I said, you can indeed model this. The efficiencies of a well-run IT shop go right to the bottom line; this is proven.
Any ROI calculation needs to consider “soft” issues such as the customer experience and effects on the marketplace. Thus, the value to the shareholder is also a result of having a good ROI from IT. Customer satisfaction goes up? That’s all a part of the metric.
To your point, IT ROI should consider how IT affects the entire organization. Indeed, in some cases it should include the removal of humans who are doing slow, costly, and error-prone manual processing. If we can automate that, all the better. But you never achieve the ROI if that has a negative effect on the core business in any way.
GR: Certainly, the efficiencies (and inefficiencies) of IT go directly to the bottom line. But, just as you say, ROI calculations need to consider the “soft” issues, and few people can agree on what the key metrics are or how to effectively measure them.
I’ve managed technology development and implementation for a couple of decades, and from year to year I’ve been asked to demonstrate my program’s contribution to ROI in terms of profit margins, price-to-earnings, return on net assets, profit before taxes, profit after taxes, reinvestment, product transitions, growth forecasts, or even inventory turnover. Boards of directors reflect and tier down the metrics that are being tracked by current or prospective investors and shareholders. Next year, they’re guaranteed to focus on a new and different set of hot-button metrics.
Technical managers tend to rise through the technical ranks, where they prospered due to their left-brain skills in deductive analysis and rational problem solving. These skills apply well in the deterministic world, where there is only a single correct answer, but they may not be of much benefit in the indeterminate world of management and executive decision-making.
Management is a right-brain skill, requiring inference, an ability to handle ambiguity, and a talent for making sound decisions on the basis of incomplete data. Technical types prefer to be graded on metrics rather than judgments when they enter management because metrics are unambiguous and present a clear challenge. However, taking the measure of an operation is usually too complicated to be reduced to a couple of numbers.
Modern managers need to be comfortable with satisfying metrics that are flowed down to them but recognize that metrics are merely decision aids, not automated decision-makers, and certainly not a replacement for the skills, experience, and judgment offered by a strong executive. Consequently, the information captured in metrics -- particularly soft metrics -- can inform the decision-making process, but responsibility and accountability for making the right judgment calls and for their consequences always rests with the executive, not with the metric.
DSL: If you’re being asked for all the figures you’ve cited to demonstrate your program’s contribution to ROI, then the people you’re working for don’t get ROI. It is, as I said, the ability for us to identify the benefit to the business, and we can do this in terms of hard savings and benefits -- real money -- as well as soft savings and benefits, like something we can track back to making the business better (for example, better customer services).
The mistake people make is over-analysis of ROI. You need only a few key measurements that reflect the business and that you can leverage consistently over time.