McKinsey authored an interesting article on how CEOs can develop a dashboard to monitor digital success. However, we believe that it is easier said than done to develop these macro-level IT metrics in an accurate, consistent and repeatable manner.
In this article, we will inspect the key challenges with 3 of the 5 metrics. This article ignores the 4th & 5th metric related to performance and retention as they are HR-related and outside the scope of our expertise and what we do as an organisation. We will focus on the challenges to the following 3 metrics:
- Return on digital investments
- Percentage of Annual Technology Budget spent on ‘Bold’ Digital initiatives
- Time to market of digital apps
Return on digital investments
The governance in most businesses enforces the discipline of key metrics such as RoI (Return on Investment) or RoE (Return on Equity) depending on organisational priorities. However, the accuracy of these metrics especially for digital projects could be highly flawed and sometimes not fully understood at the Senior management level, resulting in incorrect spend decisions.
Consider a scenario: a digitisation project that requires migration of a few applications to the Cloud.
This requires key metrics such as the current TCO (Total Cost of Ownership) of Applications, the target state TCO of the Application, Unit Cost metrics of the target state infrastructure, Decommissioning costs of the Application, Cost reductions gained by migrating the Application, Cost uplifts or reductions in the target state, etc.
All these metrics rely on the availability of
- a reasonable degree of quality of IT and Financial data
- robust IT Cost Models
- Easy to understand reports and analysis tools
However, many organisations find some or all of the above lacking thus creating a gap between top-level strategy and ground-level execution.
Percentage of Annual Technology Budget spent on ‘Bold’ Digital initiatives
Classifying the various components of the IT budget offers benefits such as a deeper insight of the costbase, and the ability to benchmark to industry peers.
There are different types of classifications:
- Financial: In this classification, the budget items are classified as Operating Expenditure and Capital Expenditure. Many organisations stop at this basic level of classification.
- RGT Model: Gartner’s Run-Grow-Transform framework is an industry-wide means of segregating the IT budget into the amount of money invest into BAU routine Operating expenditure referred to as Run costs; while ‘Grow’ refers to the portion of the Capital expenditure budget that typically delivers incremental benefits to the business; and ‘Transform’ as the label suggests is the portion of the Capital expenditure budget that is used for transformational aka ‘bold’ initiatives. Firms such as Gartner offer benchmarks that enable companies to compare against their peer group.
- Cost Category: This breaks down the costs into ‘Staff’, ‘Vendor’ and ‘Other’ categories. Staff covers people costs, Vendor covers 3rd Party expenditure and Other covers depreciation, amortisation and intercompany charges.
- Cost Pools: This classification structure breaks costs into granular levels of categorisations such as Internal Staff, External Staff, Hardware, Software, etc. Again, firms such as Gartner offer benchmarks that enable companies to compare against their peer group.
- Functional Groups: In this classification structure, IT budgets are aligned to categories such as Datacentre, Databases, Servers, etc. Each of these categories are fully loaded costs that include Staff, 3rd Party Contracts and other items such as depreciation. Again, firms such as Gartner offer benchmarks that enable companies to compare against their peer group. Further, it is also possible to generate unit cost metrics based on this classification which is beneficial to project investment decisions and benchmark comparisons.
Time to market for digital apps
Agility has been brought to the forefront due to the pandemic. Businesses have had to take quick decisions within a very short time span in order to survive or continue to remain operational.
While ‘time-to-market’ is a good metric to measure agility, we’ve realised that one needs to keep an eye on other metrics to monitor how this agility is achieved.
- Application Catalogue: Is there an increase in the number of applications in the Application Catalogue? If so, this implies that multiple instances are being deployed – likely as a result of code branches that result in increased operational costs – as each additional instance consumes its own infrastructure and resources such as staff and licenses.
- Technical Debt: Technical Debt is the implied cost of additional rework caused by choosing an easy, limited solution instead of taking a better approach that would take longer. While firms can take ‘shortcuts’ to achieve faster time-to-market, this may, in hindsight, be a more expensive solution unless the architecture allows.
A CEO dashboard to monitor the key IT metrics for digital success is a nice idea. However, execution has its challenges. The secret to overcoming these challenges lies in ensuring a firm has invested in maturing its IT and Financial data, has robust IT Cost Models in place and a tool that produces easy to understand IT metrics and analysis of the costbase.