Why your organization needs to focus on finishing

If you’ve ever run a marathon in your life, you know how much preparation, commitment and endurance it takes. Although I have never run longer than a 5k, my wife has participated in many of these tough races, including the prestigious Boston Marathon. Throughout my career in data, I’ve often compared analytics to a marathon. Similar to running one of those long-distance races, your organization must be prepared, committed, and persistent to the finish if it is to succeed with analytics.

The Data Analytics Marathon finish line is slightly different than regular races. There are no cheering crowds, no finish line ribbons and no fancy medals – your reward is the business value you generate from your data. For example, the data could reveal how a key business process could be optimized or how a costly customer problem could be solved. By comparing the analysis to a race, I do not mean that it is a unique process. Just as many marathon runners participate in multiple races each year, your analytics will go through multiple cycles as business priorities change and evolve.

During each of these cycles, your organization must go through the following stages of the data analysis marathon:

  1. Data gathering. You collect all kinds of raw data about your business operations from different sources. Much of this data will be generated automatically, whether you like it or not. Some of your data may require some thought and effort (strategy) to capture properly so that critical business questions can be answered.
  2. Data preparation. Before you can use your data, it needs to be cleansed, combined, and formatted for reporting and analysis. Without accurate and consistent data, it will be difficult to gain valuable insights from what is collected.
  3. Data visualization. To monitor business performance, your data needs to be visualized in reports and dashboards. By sharing this summary information across your organization, managers and employees will be able to observe how different aspects of the business are performing.
  4. Data analysis. To gain deeper insights into the business, your people will need to explore the data to uncover potential issues or opportunities. An iterative data discovery process will help your organization unlock insights that can improve business performance.
  5. Insightful communication. To ensure that information leads to the right decisions and actions, it must be communicated effectively. Data storytelling opens the mind of the audience to new possibilities, using engaging narratives and clear visuals to explain key ideas.
  6. Take action. The last crucial step is to decide which ideas should be pursued, and then to implement the necessary changes. In some cases, you can first deploy a test to check the results before making bulk changes. Either way, you’ll want to evaluate the results after each change and learn from it.

You will notice that I have included some percentages in the diagram. In my experience, they represent rough estimates of the number of companies that reach each stage of the data analysis marathon. Today, I would estimate that 99.8% of companies collect data, and a high percentage of these organizations also prepare reports and visualize their data on a regular basis.

However, there is a significant drop in the last mile of the race where analytics teams conduct analysis, share insights, and then implement changes to optimize the business. Most companies have no problem with starting the data analytics marathon, but many don’t finish the entire race. In fact, they’re more likely to bail out and start a new race than see an entire marathon run to completion. As a result, they are constantly running but never finishing anything.

Often, I meet senior executives who express their frustration with the lack of value they have seen from their investments in analytics. In most cases, their dissatisfaction can be attributed to a lack of focus on finishing. If your organization does not progress through all stages of the data analysis marathon, positive feedback will remain elusive.

How to Succeed in the Last Mile of Analytics

Organizations need to complete the analytics marathon to get the most out of their data investments. If your business keeps re-running the race and only executing the first part, your analytics solutions will never be profitable. While the last mile is only 3.8% of the total marathon distance, it is a crucial section that will decide whether you value the rest of your effort. To refocus your business and prepare it to conquer the last mile of analytics, I offer three suggestions:

  1. Automate tasks upstream. There is a lot of hype surrounding the introduction of artificial intelligence and machine learning capabilities throughout the analytics marathon. However, the areas where it can significantly benefit organizations are in the early stages of the process. Today, there are a host of new technologies that can automate and streamline the repetitive and labor-intensive tasks that occur during the data collection and preparation phases. If you can help your analytics team be more efficient with tasks at the start of the marathon, you can reallocate more time and energy to last-mile activities such as data mining and data storytelling.
  2. Reduce the range. Often organizations have a grand vision of what they want to accomplish with analytics. They launch big data initiatives that eventually crumble under the weight of their own ambitious scopes before any value can be generated. Rather than going high and wide with your analytics (boiling the ocean), it usually makes more sense to go from start to finish with a more focused and narrow focus. Limited scope may seem counterintuitive, but you’re more likely to generate insights and business value faster, which can build momentum for future expanded analytics efforts.
  3. Foster a stronger data culture. Your company’s existing data culture will have a huge impact on the difficulty of each analytic marathon. If your organization has a weak data culture, you’ll feel like you’re constantly on the rise. From weak management buy-in to inconsistent business processes and poor data literacy, multiple obstacles will make progress slow and difficult. Building a stronger data culture should always start with your leadership team leading by example, prioritizing data initiatives and removing internal roadblocks. Eventually, as a data culture begins to emerge, its gravity will help propel your organization through successive analytic marathons.

Running a marathon is not easy – 26.2 miles is a long distance. The analysis is not simple either and can take years to set up. Experts advise new marathon runners to run the first third with their heads, the next third with their legs then the last third with their hearts.

This aphorism also applies to data analysis marathons. In the beginning you have to to be intelligent—align your data with business strategy and leverage technology to ease the burden. In the middle you have to to be strong and rely on your domain expertise and analytical skills to uncover actionable insights. Finally, you want your employees to be inspired to act on ideas and drive positive change. Throughout the analytics journey, it’s imperative that you stay focused on the finish line so you can fully leverage all the value your data investments have to offer.

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