Keeping Strategy Execution on Track (Five Measurement Mistakes and How to Avoid Them)

While 80% of leaders feel their company is good at crafting strategy, only 44% believe this is true for implementation. According to Harvard University, a recent survey of more than 400 global CEOs found that excellence in execution was the number one challenge facing corporate leaders in Asia, Europe, and the United States, heading a list of some 80 issues.

Business intelligence (BI) solutions—in particular, dashboards developed using those tools—are often designed to support the execution of strategy. These dashboards provide a means of monitoring internal and external factors that influence success, providing insights on how execution is progressing. This information is invaluable because it enables the redeployment of resources to maintain focus on the activities and invest in the capabilities that make the biggest difference to results. These benefits are exactly why according to Gartner, global spending on BI and analytics will approach $18 billion in 2017. And yet despite all that investment in Business Intelligence, executional excellence is still the top challenge for CEOs.

During the execution phase of any strategy, it’s crucial to provide leadership with visibility to the factors that are driving or influencing success. Good measurement and reporting can highlight progress on the initiatives that influence results and provide the management team with critical insights that support more agile execution. Agility is important because it allows the team to more quickly change focus as new information comes to light. Of course, becoming more agile is not easy because it demands a higher level of comfort with change, and leaders and managers need focused, actionable and fast information to support efforts to make those changes.

Unfortunately, many companies are getting lost in the complexity of getting their arms around the big data revolution by taking a bottoms-up approach to data management and analysis. This approach results in data-related initiatives that are too large in scope, take too long, have a higher risk of failure, and deliver a lower ROI. The leaders that embark on this journey will find that prioritization pays higher dividends and delivers real value on an accelerated timeline.

In our experience, companies with good measurement and execution tie their efforts directly back to the strategy, and focus on the critical few areas where they can identify, understand and react to changes quickly. Some years ago, Jeff Bezos communicated the Amazon retail strategy to his team by sharing three very simple customer preferences: lower prices, bigger selection, and faster delivery. Each customer preference can be addressed by pulling on certain organization levers that can be readily measured—and that’s exactly where organizations like Amazon set their priorities for measurement.

This diagram, called a “value tree,” can be further developed to the right depending on how deep you want to go (e.g., local inventory on-hand requires warehousing facilities that are close to population centers, which in turn requires the efficient build-out of each facility). Unfortunately, organizations often start with the data they have or the infrastructure they think they need and not the business problem they’re trying to solve. In our experience, the five most common mistakes organizations make in building out their measurement infrastructure are:

Focus on too much too soon. Organizations often start by seeking to measure everything that can be measured in order to satisfy all needs. This introduces unnecessary complexity not only to the project, requiring higher levels of resourcing, but also to the dashboard itself, making it much less useful.
Develop the wrong measures. The infrastructure is created from the bottom up instead of starting with the essential needs of the business. Starting from the bottom almost guarantees that the process will be exploratory rather than strategic, and much less efficient.
Allow data quality to overly influence the approach. Data is never perfect, and few organizations have everything they need to measure with perfect accuracy. Some analytics leaders use data quality challenges to explain why dashboards don’t effectively support decision-making, or to stop measurement development altogether, rather than seeing an opportunity to identify and address what’s broken in the measurement process.
Emphasize technology at the expense of value and impact. Real-time data, embedded analytics and self-service enablement are incredible business intelligence technologies. But displaying data faster or better is not what dashboards are built to do. If they are not closely tied to what a user needs to make good decisions, these technologies can be expensive distractions.
Choose cool displays over useful information. How the measure is defined, the types of charts used to display information, data filters applied and the timeframe for presentation can all influence the utility of the dashboard. Many organizations spend a great deal of time iterating on data visualizations that provide interesting views of the data, but do not tie those visualizations to the decisions they need to make.

Strategy development and execution is all about making decisions on the future direction of the organization; business intelligence is about providing insight to inform those decisions. If these things are not tightly connected, then dashboards at best become an unnecessary complication and, at worst, a misleading distraction. But there is a relatively simple, five-step process that is both efficient and delivers high-impact results.

Start with the business strategy. Whatever the organization’s strategy, start by identifying the specific things the organization will need to achieve in order to execute against it. Both dashboard developers and business users must be prepared to frame their interactions in terms of how the organization will get there.
Identify the critical drivers of value. Build a value tree by determining which capabilities you need to have, or the activities you need to perform well, in order to execute effectively. Then determine which of those are most important. This exercise of unbundling the organization’s strategy establishes a direct link to the strategy and prioritizes what leadership needs to monitor.
List related questions and decisions. Focusing on the critical drivers, list the most important questions that need to be asked and answered and the key decisions that will need to be made. Taking the time to understand how leaders and business users will actually use the dashboard is critical to getting the focus and design right.
Define the measures that matter. Identify the measures that will provide the information needed for each question and decision, and then determine the primary data source and format required. This is the opportunity to identify and address gaps in data availability and quality. Again, everything you do here ties back to the strategy so investments made at this point will be highly targeted and impactful.
Develop designs that present information in ways that draw out key insights and address a number of different business scenarios. Review and iterate designs with leaders and users and constantly test for utility. Develop a design that supports decision making.

Applying these five simple steps will give your team the information they need to more effectively monitor and adjust the execution of your strategy, leading to higher growth, profitability and realization of organizational goals.

By Donncha Carroll, November 22, 2017