In our age of analytics, more and more companies claim to be data-driven. They’re proud of having largely abandoned experienced-based, gut-feel-based or boss-directed decision making.

The value of data-driven decision-making is that it improves the quality of business decisions while reducing the risk of poor, business-killing decisions caused by:

  1. Simply following the views of the loudest, most charismatic or most dynamic person in the room.
  2. Inadequate data quality and lack of data integration in company systems.
  3. Using inadequate analytic tools or relying solely on Excel.
  4. Over-reliance on anecdotes from operations.
  5. Relying largely on the person with the most seniority or experience.
  6. Over-reliance on a valued consultant or executive mentor.
  7. Taking the path of least resistance based on tradition.
  8. Cautiously following industry trends.

Since data-driven can be defined in many different ways, here are the widely-accepted indicators that will enable you to gauge how systematically your company operates using a data-driven culture.

Business strategy is underpinned by data

Companies often struggle to develop a coherent business strategy. Some companies are distracted by the latest headline, executive turnover, competitor initiatives, internal turmoil or regulatory developments. For example, can Bombardier reasonably claim that its development of the C Series jet was a data-driven strategic decision in view of the existence of strong, direct competitors?

Data-driven companies develop strategy by integrating the data about business measures, technology, external trends, and threats into a single, unified approach. They use data and analytics to describe how the strategy will:

  1. Produce business value for shareholders.
  2. Deliver product and service value for customers.
  3. Leverage technology developments and process improvements.
  4. Address threats posed by competitors.

Innovation and market disruption are evident

Companies cannot rely on previous successes to drive todays and future prosperity. Eventually, competitive advantages become commoditized and innovation, expressed as appealing products or services, will be necessary to sustain growth.

Innovation is a necessary trait of sustainable companies. Data-driven companies analyze a wide variety of data to:

  1. Stimulate new ideas.
  2. Model the potential and risks of innovations.
  3. Create new revenue streams from promising innovation.

Data and analytics are widely embraced

Many companies make use of data and analytics quite unevenly. Some functions or divisions use it widely while others remain skeptical about the value. For example, a company may say they use data to drive decisions but in reality some managers still follow their instincts and dismiss the analytical results as nice but “not for me.”

Data-driven companies that use data and analytics frequently and consistently in driving decisions is indicated by:

  1. Data being widely recognized as a valuable asset.
  2. Diversity of data and analytical models being used.
  3. Staff searching for new types of data from additional internal and external sources.
  4. Internal presentations containing a significant number of charts and not just bullet points.
  5. Application of mature asset life cycle management principles.

Measurements quantify appropriate KPIs

Many companies struggle to identify, define, and measure appropriate key performance indicators (KPIs). In some companies enormous political advantage can be derived by revising existing KPIs or by introducing magical new KPIs to create the illusion of superior performance.

By contrast, data-driven companies apply sound measurement principles to KPIs. Supporting evidence consists of:

  1. How well feedback, provided by the data underlying the KPIs and analytical models, is used to improve business or process performance.
  2. How well managers and employees maintain situational awareness to ensure risks are mitigated as quickly as possible.
  3. Managers that use predictive models to become proactive in their decision-making style.
  4. How well lessons from historical operations are used to make smarter decisions in the future.

Scenarios and tests are widely used

Many companies can’t find the resource or the time to examine the data they collect more than superficially. This situation leads to poor decision-making with too much reliance on intuition or hoping that the past is a useful guide to the future.

Data-driven companies that routinely create scenarios and revise assumptions to discover new relationships or to remove biases from critical decisions is indicated by:

  1. Frequent tests to evaluate scenarios and alternatives.
  2. Competitive and trend research using external data.
  3. Analysis using a wide range of data and analytics techniques.

Staff and teams communicate and share information

In many companies communication is confined to silos. Similarly, data is not shared due to internal competition or technical barriers. Such companies are unlikely to be data-driven.

Data-driven companies exhibit a more sharing and more open culture that is transparent to stakeholders.

Based on these indicators, is your company data-driven? Would adopting a more data-driven culture strengthen your company’s performance?

What is your experience with data-driven decision-making?

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