12 Tips for Better IT Decision-Making Using Experience Data

This blog shares twelve tips for better decision-making using experience data.

Tips for Better Decision Making

So you’ve been convinced of the importance of experience data and insight to IT decision-making, but what must you do to make it a reality? There’s already helpful content across our website related to the introduction of experience management and the collection and analysis of experience data. For example, the IT Experience Management (ITXM) Framework™, ITXM Best Practices Library, and ITXM Foundation Course and Certification.

However, this helpful guidance can be seen as a subset of the IT decision-making “bigger picture,” with the collection and analysis of experience feedback only the start of the associated decision-making efforts. To help, this blog shares twelve tips for better decision-making using experience data.

The power of experience data

When an IT organization starts collecting experience data, it might view the activity as part of what’s needed to improve employee or end-user experiences (and their productivity as a result). This is true. However, the benefits of experience data and insights can go beyond tactical IT service delivery and support improvements to influence higher-level IT thinking, decision-making, and strategizing.

Experience data unlocks a different perspective of IT’s performance in the context of end-user needs and expectations. It also drives cultural change that influences future changes within the IT organization – for example, refocusing IT priorities from traditional and trend-based improvements to changes that will improve business operations and outcomes (based on experience feedback).

Using experience data to drive IT decision-making

Effective IT decision-making using experience data involves analyzing historical end-user feedback and technical performance data to inform and guide decisions. But more is needed. Here are twelve tips that will improve your IT decision-making using experience data:

  1. Gain buy-in to the power of data-driven, or data-informed, decision-making. It might seem an obvious point to state, but the use of experience data in driving IT decision-making requires an understanding of how data-driven decision-making delivers superior corporate results. Without this, the opportunity of experience data and insights is dulled.
  2. Appreciate the higher-level opportunities of experience data. As already mentioned, end-user experience data is great for identifying tactical improvement opportunities. For example, changes to IT self-service portal capabilities that improve usability, outcomes, and adoption levels. However, this is just the start of the improvement journey, with experience data and insights offering the ability to improve strategic IT decision-making too.
  3. Engage business stakeholders (and not only at the outset). As with any organizational change, involving relevant business stakeholders is vital to introducing experience management. However, this engagement is relevant throughout the decision-making process to help ensure all perspectives and needs are considered.
  4. Start experience management efforts with clear objectives. Again, this might sound like an obvious statement. However, focused experience management initiatives will deliver more significant benefits than introducing experience management capabilities as a “good thing to do.” These objectives might change over time, but they will also inform the IT decision-making that’s driven by the experience data and insights.
  5. Collect as much data as possible (at least at the outset). This is the experience feedback from end-users that articulates their IT experiences and highlights IT service delivery and support issues and pain points. It’s also the technical data available from the corporate IT service management (ITSM) tool that adds context to and enhances the “human-perspective data set.”
  6. Leverage analytical techniques to identify issues and trends. Root-cause analysis techniques should be used to look past the visible symptoms of issues to understand the underlying causes. Predictive analytics can also forecast future issues, and machine learning algorithms can identify patterns and correlations that are not immediately obvious “to the human eye.”
  7. Compare company performance against industry benchmarks. While period-on-period trend analysis can validate or identify improvement opportunities, it’s essential to understand the experience data and insights in context. For example, and as shown by HappySignals’ analysis of aggregated customer data, end-user experience can vary significantly across regions and industries. Such that what might seem like an improvement opportunity is, in fact, simply the norm (or the reverse could be true).
  8. Assess experience-based improvements in the context of traditional decision-making factors. For example, cost-benefit analysis can compare the potential costs and benefits of different decision options, and risk management techniques can evaluate the risks associated with each decision option. These and other factors aid the prioritization of potential improvement opportunities (along with the alignment with strategic corporate goals).
  9. Provide transparency in decision-making. Transparency is a crucial aspect of experience management success. This should also be applied in decision-making – by clearly communicating how and why decisions were made.
  10. Promote agile decision-making. Don’t “set decisions in stone.” Ensure that decisions can be adjusted as more information becomes available or circumstances change.
  11. Measure and communicate the impact of experience-driven decisions. After experience-driven improvements are made, it’s essential to measure their impact. This feedback loop helps validate decisions and demonstrates the return on investment (ROI) of prioritized improvement initiatives.
  12. Elevate proven tactical decision-making using experience data to strategic decision-making. Your organization might find that this evolves organically rather than being a deliberate change. For example, a series of IT service desk improvements based on experience data will likely change the thinking related to IT support provision – perhaps from ticket handling to employee enablement. This change in thinking and cultural aspects will also bring experience data and insights into more strategic IT support decision-making.

If you want to learn more about using experience data and insights for better IT decision-making, take a look at our ITXM platform.

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