{"id":9004111224888265,"date":"2023-05-16T14:24:39","date_gmt":"2023-05-16T14:24:39","guid":{"rendered":"https:\/\/www.pragtestdomain.com\/resources\/?post_type=resources&p=9004111224888265"},"modified":"2024-01-12T19:59:34","modified_gmt":"2024-01-12T19:59:34","slug":"avoid-these-mistakes-when-prioritizing-data-projects-for-your-company","status":"publish","type":"resources","link":"https:\/\/www.pragmaticinstitute.com\/resources\/articles\/data\/avoid-these-mistakes-when-prioritizing-data-projects-for-your-company\/","title":{"rendered":"Avoid These Mistakes When Prioritizing Data Projects for Your Company"},"content":{"rendered":"

Even in a world full of data, business decisions often still rely on instinct and emotions. However, when it comes to business, considering all external factors before making a move is essential. This is where data-driven decision-making steps onto the stage.<\/span><\/p>\n

Data-driven decision-making is a strategic business approach that leverages factual data and insights to align with organizational goals, strategies and initiatives. Making informed decisions based on data significantly increases the likelihood of achieving success.<\/span><\/p>\n

In this comprehensive guide, we delve into the techniques to prioritize data-driven projects effectively, enriched with case studies that exemplify the power of successfully prioritizing data projects.<\/span><\/p>\n

Prioritizing Data Projects with Business Aspirations<\/b><\/h3>\n

Imagine investing in projects only to realize they don’t sync with your strategic objectives, leading to wasted time and resources. To prevent this, effective project management is paramount. <\/span>It involves charting a long-term vision and creating specific, measurable tasks to realize that vision<\/span><\/a>. Once the objectives are crystal clear, it’s crucial to ensure that resources, tools and processes align with them.<\/span><\/p>\n

Let’s consider a well-known brand, Excellus BlueCross BlueShield. They struggled with visibility into their resource capacity due to inaccurate data, which led to suboptimal project choices. The introduction of portfolio and resource management improved their data quality. As a result, they <\/span>reported a 99% timesheet submission rate, and senior leadership gained better visibility into portfolios<\/span><\/a> for compliance assurance.<\/span><\/p>\n

The Power of Key Performance Indicators\u00a0<\/b><\/h3>\n

Closely monitoring your key performance indicators (KPIs) and checking them regularly is pivotal. This entails weekly, monthly or quarterly reviews of charts, graphs and summary data. By doing this, you can drive your business or department towards achieving sustainable profits.<\/span><\/p>\n

Choosing the Right KPIs for Your Data Projects<\/b><\/h3>\n

Defining which KPIs are vital for your business involves a clear understanding of your goals<\/span><\/a> and avoiding the trap of vanity metrics. <\/span>Here’s a tip: concentrate on no more than 3-5 company goals within a 12-month period.<\/b><\/p>\n

Consider a support team analyzing trouble tickets. A quantitative KPI might be Time to Resolution. However, if this number exceeds the target, it could indicate inefficiency in resolving customer issues. Adding qualitative data, like customer feedback, might reveal that the team is actually thorough when tackling complex and multi-step problems.<\/span><\/p>\n

Assessing Data Maturity to Prioritize Projects<\/b><\/h3>\n

A data maturity model outlines the <\/span>key stages a company must undergo to achieve data maturity<\/span><\/a>. This model includes various elements, each with its specific definition, detailed explanation, and criteria for attainment.<\/span><\/p>\n

Your company can elevate its data maturity level<\/span><\/a> by understanding its current position on the data maturity journey. This involves asking questions like:<\/span><\/p>\n