How Success Should Be Defined for an IT Department in an Organization

How Success Should Be Defined for an IT Department in an Organization
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Defining success for an IT department based on meeting goals and Key Performance Indicators (KPIs) can lead to steadier, more measurable long-term improvement for the entire organization. KPIs also allow IT departments to effectively track pertinent data and more efficiently address any challenges that may crop up. 

The value of being able to effectively track performance and identify course corrections needed to meet organizational goals may be why nearly 75% of all IT executives believe IT analytics is important – or even critical – to their operations. 

To use IT analytics productively, you first need to understand the unique challenges your department and overall organization face, and how they can be addressed.

What Challenges Does Your IT Department Face?

While there are unique challenges that are specific to your organization, there are also common challenges that just about every business and IT department face. Some of the top challenges faced by many Numerify customers include:

  • Improving productivity (e.g., are developers doing too much unplanned support work?)
  • Achieving high reliability (e.g., how can we mitigate the drivers of change failure?)
  • Automating IT Operations (e.g., which common requests should we automate?)
  • Accelerating development delivery (e.g., where are the bottlenecks in our Agile / DevOps value stream?)
  • Improving Business IT Alignment (e.g., How well are IT Services meeting customer needs?)

While these and other challenges are common in nearly every industry, there are also unique IT challenges your organization will face. These challenges must be identified and noted, and prioritized based on their relative importance and magnitude.

How to Define Your KPIs

Once your key challenges have been identified and prioritized, it’s crucial that your team identifies KPIs to baseline performance and find effective methods of resolving issues. Similarly, metrics that are tracked must directly support KPIs your organization has set to address business challenges. Otherwise, they don’t serve a purpose. 

Depending on the challenges that have been identified and selected to be addressed, you may set KPIs for:

  • Service management and optimization
  • Change success and risk
  • DevOps Performance Management
  • Project and Portfolio Optimization
  • Business Service Health
  • Asset Risk and Governance
  • … And others. 

One of the most important things to remember is that goals and KPIs are separate. KPIs are data-reliant. Goals can be more abstract, but should still be dependent on KPI performance. 

For example, if you have a goal to improve Business-IT alignment, you may set a KPI for reduction in Change Lead time. If you see an improvement in metrics like Change Failure rate and number of Changes implemented, you could use these as supporting evidence for why Change Lead time was reduced in a manner that improves Business-IT alignment. 

Use an IT Business Analytics Solution to Track Metrics and Meet Your KPIs

Get a view of your end-to-end journey. Only about 40% of IT executives use a third-party IT analytics application that gathers data and automatically correlates metrics to set KPIs.

Numerify allows you to track metrics in real time so you can stay on top of your goals and know if you’re meeting KPIs. Download our buyer’s guide today to find the right IT business analytics solution for your organization so you can set goals and KPIs to create a real plan for defining success for an IT department.

Use an IT Business Analytics Solution to Track Metrics and Meet Your KPIs

The term “predictive analytics” once served to illustrate the horizon of machine learning, but organizations quickly learned that making predictions did not always provide the information needed to react to the possible future. To achieve that, machine learning is needed to process potential outcomes and recommend one that provides the optimal mixture of opportunities with minimal risks.

In other words, prescriptive analytics uses predictions based on past data to uncover future opportunities. They generate recommendations for the optimal path with minimal risk and maximum chances of net positive outcome. On a day-to-day basis, prescriptive capabilities can serve to make IT workflows more efficient while reducing costs. 

For instance, by clustering related incidents, IT leaders can learn that some types of incidents have a common root cause and resolution that could be handled by a lower support tier if they were enabled by a knowledge base article. By identifying the “next best action” for incoming incidents, teams can “shift left” to lower level teams, freeing up resources and allowing higher-level teams new opportunities to focus on more important issues.

To achieve true prescriptive capabilities requires more advanced AI models tuned through machine learning and customized to your specific data sources, environment, and market niche. The proper structure of source information can be more important than the specific technology used.

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