Can your data be trusted?

Can your data be trusted?

60% of executives don’t trust their data, according to a data-health survey. Clearly the importance of data to business success is well understood, however knowing the importance doesn’t automatically translate into data that can be trusted.

To be successful in today’s constantly changing and highly competitive business environment, organisations need to be committed to data. It should be at the centre of every business decision in order to achieve competitive advantage. But it’s easier said than done: having the data is not the same as knowing what to do with it. And data needs to be 100% reliable.

Ramifications of unreliable data

The earlier statistic highlights that a large percentage of leaders and executives continue to make decisions based on gut and other intelligence from within the organisation. The ramifications are staggering:

  • Excessive time, energy, and resources are being wasted
  • Mountains of data is being produced that is not needed, wanted, or trusted
  • Decisions are being made based on bad, incomplete, or untrusted data
  • Poor decision making
  • Lost opportunities
  • Poor customer experience, resulting in lost revenue

If business leaders are focused on achieving organisational goals such as:

  • Decreasing the cost of operations
  • Improving efficiency
  • Increasing revenue
  • Improving customer service and customer retention
  • Increasing margins
  • Doing more with less

then they need to focus on the right data and data they trust, which can be used throughout the organisation; data transparency.

Why do decision makers not trust their data?

There is a lot of executive inertia to move to data-driven decision making, where historically decisions were made based on experience from the past. In today’s volatile business environment, predicting the future based on past experience is not enough, and doesn’t work. Part of the biggest challenges in the paradigm shift to data-driven decision making is data efficiency.

Savvy business leaders and decision makers expect data to be timely, accurate, and consistent. The key reasons cited for data distrust are:

  • Timeliness
  • Accuracy
  • Consistency
  • Accessibility
  • Completeness
  • Uniqueness
  • Validity

They expect it to be easily accessible and complete. And that’s understandable, when even a small amount of bad data can lead to a poor business decision that may lead to catastrophic business results and outcomes.

Data trust means having confidence that your organisations data is healthy, and ready to act upon. But it’s not simply the raw data, it’s the analytics and insights that are derived from the data. That’s where the real power and value of data-driven decision making is unleashed.

Building data trust

Trust also comes from ensuring that everyone across the business recognises the critical role that data plays within the organisation; from supply chain to marketing, new product development to customer experience.

Data is constantly being produced from a myriad of systems and processes. Data about employee efficiency, customer usage, point of sale, data from software systems, websites, marketing initiatives… the list is endless. Data can come from inside the organisation as well as outside the organisation and may include purchased data. Different systems and process generated data means unstructured as well as structured data that needs to be consolidated and enriched.

To deliver on data trust, organisations need to implement and automate processes for auditing, assessing and cleaning their data. Complete data trust requires a data infrastructure, that combines human processes alongside software in order to move the dial to a data-centric organisation, with data that executives trust.

A framework for data trust, that makes data your greatest assets (other than your people), requires:

  • Data certaintyis the data accurate?
  • Understandinghow the data is prepared
  • Consistencymake sure the data is clean, complete and consistent
  • Timelinessis the data current, up-to-date?
  • Accessibilityis the data accessible and supported with appropriate insights and dashboards for ease of understanding?
  • Traceabilitycan the source of the data be tracked? This is particularly important when we bring data from disparate systems together and managing structured and instructed data

The primary difficulties relating to trusting your data relate to locating, integrating and cleaning the data, in order to interrogate and support data-driven decision making that adds significant value across the organisation.

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