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What metrics can IT Managers use to evaluate their team's decision-making skills?

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Decision-making is a crucial skill for IT Managers, as they have to deal with complex problems, multiple stakeholders, and uncertain outcomes. However, measuring and improving this skill can be challenging, as it involves both quantitative and qualitative aspects. In this article, we will explore some metrics that can help IT Managers evaluate their team's decision-making skills and provide feedback for improvement.

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1 Quality of decisions

One of the most obvious metrics to assess decision-making skills is the quality of the decisions themselves. This can be measured by looking at the results and impacts of the decisions, such as customer satisfaction, revenue, efficiency, security, and innovation. However, quality alone is not enough, as some decisions may have positive outcomes by chance or external factors, while others may have negative outcomes despite being well-informed and rational. Therefore, quality should be complemented by other metrics that reflect the process and criteria of decision-making.

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2 Speed of decisions

Another metric that can indicate decision-making skills is the speed of decisions. This can be measured by tracking the time it takes to make and implement decisions, as well as the frequency and urgency of decisions. Speed is important, as it shows the ability to cope with pressure, prioritize tasks, and act on opportunities. However, speed should not compromise quality, as hasty or impulsive decisions can lead to errors, conflicts, and risks. Therefore, speed should be balanced by other metrics that reflect the accuracy and consistency of decision-making.

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3 Data-driven decisions

A third metric that can enhance decision-making skills is the use of data-driven decisions. This can be measured by looking at the sources, methods, and tools of data collection, analysis, and visualization, as well as the alignment of data with goals, objectives, and strategies. Data-driven decisions are valuable, as they provide evidence, insights, and feedback for decision-making. However, data-driven decisions should not ignore intuition, creativity, and experience, as these can also contribute to decision-making. Therefore, data-driven decisions should be integrated with other metrics that reflect the human and contextual aspects of decision-making.

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Rouzbeh Beikpour

Founder of Roulium | IT & Digital Marketing Leader | Transforming Businesses with Scalable Solutions
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- Data Accuracy: Assess the accuracy of the data used in decision-making. - Data Utilization: Measure how effectively the team leverages data to inform decisions.

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4 Stakeholder involvement

A fourth metric that can improve decision-making skills is the involvement of stakeholders. This can be measured by looking at the communication, collaboration, and consultation of decision-makers with internal and external stakeholders, such as team members, customers, partners, and vendors. Stakeholder involvement is beneficial, as it increases the diversity, transparency, and buy-in of decision-making. However, stakeholder involvement should not create confusion, conflict, or delay, as these can hinder decision-making. Therefore, stakeholder involvement should be managed by other metrics that reflect the leadership and governance of decision-making.

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Grzegorz Babicz

? Experienced IT Consultant / Project Management
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Collecting feedback from internal and external stakeholders in organisation to gauge their satisfaction with the team's decisions.

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5 Learning and adaptation

A fifth metric that can foster decision-making skills is the learning and adaptation of decision-makers. This can be measured by looking at the feedback, evaluation, and reflection of decision-makers on their decisions, as well as the actions, changes, and improvements they make based on their learning. Learning and adaptation are essential, as they enable decision-makers to recognize their strengths and weaknesses, learn from their successes and failures, and adapt to changing situations and expectations. However, learning and adaptation should not lead to complacency, inertia, or resistance, as these can impair decision-making. Therefore, learning and adaptation should be motivated by other metrics that reflect the growth and innovation of decision-making.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Chris Burgess

Global Vice President of Technology and Deputy CIO - Infrastructure, Cloud Platform, Enterprise Engineering and Corporate IT at Expedia Group
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Outside of the metrics themselves, in my experience it is important to publish your metrics across the organisation , this transparency drives accountability, removes potential for perception issues and ensures alignment on the right metrics. Start with a simple scorecard, include aspirational metrics that you might not yet have measures for and evolve and iterate…. We’re currently looking at Atlassian Atlas as a way to share roadmap updates, alongside dashboards that are automated on the most important metrics (for me this is a combination of OKRs progress, Operational health/hygiene metrics and financial adherence metrics )

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What metrics can IT Managers use to evaluate their team's decision-making skills?

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6

1 Quality of decisions

2 Speed of decisions

3 Data-driven decisions

4 Stakeholder involvement

5 Learning and adaptation

6 Here’s what else to consider

IT Management

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What metrics can IT Managers use to evaluate their team's decision-making skills?

1

2

3

4

5

6

1 Quality of decisions

2 Speed of decisions

3 Data-driven decisions

4 Stakeholder involvement

5 Learning and adaptation

6 Here’s what else to consider

IT Management

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