Digital KPIs: The secret to measuring transformational success

Regardless of where organizations are in their digital transformation, CIOs must provide their board of directors, executive committees, and employees definitions of successful outcomes and measurable key performance indicators (KPIs).

Do a little research, and you’ll find many frameworks, taxonomies, and recommendations for digital KPIs. For example, McKinsey suggests five metrics for digital CEOs, including the financial return on digital investments, the percentage of leaders’ incentives linked to digital, and the percentage of the annual tech budget spent on bold digital initiatives. Deloitte has a taxonomy of 46 digital transformation value KPIs but acknowledges that 26 are used by fewer than 55% of organizations. MIT warns that the wrong KPIs can doom digital transformation and recommends a portfolio of enterprise KPIs that measure business value delivered by the transformation.

Selecting KPIs can thus become a paradox for CIOs who know that having no KPIs, too many metrics, or investing in the wrong ones are all problematic.

“What gets measured gets managed, or put another way, your results will be determined by what you are measuring,” says Martin Davis, CIO and managing partner at Dunelm Associates. He suggests, “Choose what you measure carefully to achieve the desired results. Keep the number of metrics small and manageable, ideally three or four, and at most seven key ones because people cannot focus on multiple pages of data.”

Aligning KPIs to key digital objectives

CIOs should look for meaningful business metrics that employees can understand — and establish practical tools for measuring them. Digital transformation metrics should capture how well the digital transformation drives business outcomes, which initiatives deliver value, and how well the organization adapts its culture and operating models.    

Focusing on those three key digital transformation objectives, CIOs can simplify the selection of their digital KPIs by considering the following:  

1. The digital transformation strategy defines how the organization realigns its targeted markets, creates new business models, and evolves its operations based on evolutions in customer expectations, technology capabilities, and the impact of data, analytics, and AI. As a result, outcome-based metrics should be your guide.
2. The portfolio of digital transformation initiatives often includes programs targeting growth, efficiencies, and improved end-user experiences, but adequate evaluation of outcomes requires program leaders to select KPIs specific to each initiative.
3. The culture transformation and evolutions in digital core competencies that CIOs target as their new collaborative operating models require KPIs to guide executives on where to focus leadership efforts, communications, and process improvements.

These objectives overlap and are interdependent, but separating them in this way highlights the three steps CIOs should take to ensure their KPI strategies align with their three objectives.

1. Define outcome-based strategic KPIs

Because executives and board members want to know how effective the digital transformation is toward overall strategic goals, CIOs should select KPIs that demonstrate outcomes driven by how well the portfolio of digital transformation initiatives performs. KPIs to consider should come from the following categories:

• Growth metrics can link revenue to a digitally enabled product or sales channel. For example, in media and ecommerce, CIOs may select revenue growth from digital subscriptions and advertising.
• Efficiency metrics might show the impacts of automation and data-driven decision-making. For example, manufacturers should capture how predictive maintenance tied to IoT and machine learning saves money and reduces outages.
• Customer and employee experience metrics can be measured through satisfaction surveys (CSat and Esat), sentimental analysis on social media, account-based revenue growth, and employee retention metrics. The art is asking the right questions and connecting experience metrics to the digital strategy and prioritized initiatives.
• Quality metrics can be used to measure the improvements that come from reducing defects, lowering the impacts of human errors, improving data quality, and other program outcomes that illustrate how increasing quality connects to business impact.
• Risk reduction metrics can focus on security, business continuity, and compliance functions impacted by technology, data, and process improvements.

In discussing digital transformation KPIs at a recent Coffee with Digital Trailblazers event, John Patrick Luethe, managing partner at Redapt, said, “Many digital transformations are forced on organizations, for example, to stay relevant in a competitive environment, respond to compliance requirements, adjust to natural disasters, or to avoid technologically driven disruption.”

In these circumstances, CIOs may want to narrow their outcome-based KPIs to the ones most likely to impact their challenges and signal to employees what’s critically important.

2. Empower digital trailblazers to align initiative KPIs

After defining and communicating the above outcome-based metrics, CIOs should leave it to the digital trailblazers leading individual transformation initiatives to propose KPIs for their programs. By defining at least one growth, efficiency, experience, quality, and risk reduction outcome-based KPI, digital trailblazers shouldn’t find difficulty in aligning with at least one of the strategic goals.

For example, here’s how Arvind Joshi, chief operating officer for global technology and co-head of public cloud at JPMorgan Chase, defines KPIs for the bank’s multi-provider cloud strategy: “We focus on measuring our progress against what we set out to do with a balanced view across our results and challenges. We track KPIs on execution (on-time delivery, cycle time for adoption), risks, outcomes for benefits (time to market, change failures, major incidents), and costs (TCO before and after adoption).”

Joshi says his teams leverage existing KPIs that reflect the overall technology strategy and add new ones for cloud best practices such as finops. He adds, “This approach to cloud metrics reinforces our long-term priorities for technology, keeps a single operating model across both cloud and on-premise, and influences the mindset and behaviors of our application teams to balance speed, cost, and stability together as they build and run code.”

During the Coffee Hour, Dunelm’s Davis suggested digital trailblazers not only consider what to measure but when to measure it. He recommends selecting adoption metrics and capturing end-user satisfaction scores for transformation initiatives impacting customer or employee experiences. But he warns about the productivity dip that occurs to support change management and suggests timing KPI capture to help identify how to reduce the dip’s duration and magnitude.

Joe Puglisi, a former CIO who is now an investor, advisor, and board member, suggests documenting leading indicator metrics at the initiative’s start because you don’t always have a perfect picture of the outcomes in the early planning stages. Productivity improvement from initiatives that deliver automation are good examples given that the impacts may not be realized until employees shift to more value-added working areas. Puglisi also warns, “Avoid defining KPIs late in the delivery process as it can lead to torturing the data until it says what the leaders want.”

3. Define velocity KPIs for transforming culture and competencies

The third focus of digital transformations is changing the culture and developing digital and transformational competencies throughout the workforce. These areas are often enablers that can impact the time to business outcomes, their magnitude, and whether they deliver ongoing results.

Joanne Friedman, PhD,  CEO, and principal of smart manufacturing at Connektedminds, suggests using three value-based KPIs: time to data, time to decision, and overall time to value. She says, “The goal of any transformation initiative should be to improve the overall value of the corporation to its customers and trading partners. Successful transformation delivers more employee and customer value faster and at lower cost. Measuring value with velocity more appropriately reflects gaps, progress, and overall improvement.”

Here are some examples that illustrate these KPIs:

• Investments in dataops, data quality, and workflow automation can impact time to data. Faster time to data can improve efficiencies, for example, by changing manufacturing output when there are shifts in buying demand.
• Time to decision can be impacted by citizen data science, transforming with agile methodologies, and other culture changes that enable front-line decision-making. Faster decision-making can impact sales, for example, when retail managers use dashboards to change product placements and pricing based on local conditions.
• Agile and devops practices that reduce cycle time to deliver features and enable continuous deployments are actions that impact time to value. Improving this KPI means teams can experiment faster, personalize experiences, and increase revenue from software-enabled products and services.

Puglisi reminds CIOs that communication is the most universal transformational competency that impacts digital transformation outcomes and culture. “Let employees know what is going to happen and recognize that people need to hear something about a change at least seven times before remembering it.” Measuring employee engagement levels is one way to validate whether people hear and understand digital transformation’s vision, strategy, and objectives.

While I offer a simplified approach to selecting digital transformation KPIs, getting everyone to align on objectives is not easy. More importantly, target outcomes and prioritized initiatives evolve, so the KPIs must evolve with the continuously transforming enterprise. Adopting a methodology that supports top-down and bottom-up alignment means more people can focus on planning and delivering outcomes rather than debating what and how to capture optimized metrics.