What KPIs should data analysts track to monitor strategic goals?

Understanding the business context is a critical. 1. Understanding Strategic Goals: Knowing the organization's strategic goals helps in selecting KPIs that are aligned with these objectives. For instance, if a company's goal is to expand its market share, relevant KPIs might include sales growth rates, market penetration metrics, and customer acquisition rates. 2. Identifying Stakeholders and Decision-Makers: Different stakeholders may have different priorities. A CFO might be more interested in cost savings and ROI, while a marketing head might focus on customer engagement. 3. Supporting Decision-Making Process: The ultimate goal of tracking KPIs is to provide actionable insights that support decision-making.

Understanding the organization's strategy and targets is crucial before producing KPI-related data. A robust grasp of key economic drivers helps prioritize a few meaningful KPIs, examining potential correlations. Many organizations focus on numerous KPIs without linking them to key performance initiatives. KPIs can be disaggregated into granular components, providing insights into specific levers that require attention, ensuring a nuanced understanding of factors influencing strategic goals. In summary, aligning KPIs with organizational strategy, concentrating on pivotal economic drivers, and establishing clear connections to performance initiatives are vital for effective data analysis in monitoring strategic goals.

An analyst must align KPIs with the business stage and direction. In startups, focus on new users, customer acquisition costs, retention, bugs, and customer complaints. These metrics are crucial for early growth. In the case of manufacturing companies, part of complex supply chains and facing market shifts, track inventory levels, temporary worker numbers, and cash flows. Businesses fighting market pressures should prioritize expense control and new customer acquisition. Remember, KPIs aren't universal. They need to be tailored and re-evaluated with each business cycle, ensuring they stay relevant and aligned with evolving goals and challenges.

?? Understanding the Business: Context is King (or Queen ??)! As analysts, our superpower isn't just crunching numbers; it's understanding the WHY behind them. ?? Strategic Goals: Above Our Paygrade? Maybe, But Still Crucial Strategic goals are set by the C-Suite. They are captains steering the ship; we're navigators plotting the course. We ensure our analysis aligns with the goals. We might not be in the room where it happens (cue Hamilton soundtrack ??), but our work supports those decisions. ?? Feedback: Your Secret Weapon If a KPI is a poor choice, speak up. Sending feedback up the chain is daunting, but someone's gotta tell the emperor he's not wearing clothes. But do it with data, not just gut feelings!

Be intentional and strategic behind the “why” of every KPI, and not just because you want to know a number. In many cases, if you have a handful of really good metrics, you’re set. You don’t need to measure everything because you’re likely not going to use all that information and it’s a time suck for analyses / not meaningful enough for an ROI. Most KPIs should be actionable, especially if your data sources come from users. You don’t want to waste their time on capturing the kitchen sink if you’re not going to strategically do anything with the data. Additionally, be very thoughtful about identifying leading and lagging indicators as these can be powerful in activating strategies that can course correct in acute areas at the right time.

-Ensure every KPI can be tied to either Revenue/Expense/Profit. It does not matter how many widgets you make if they are not sold. Real dollars are what matter in the end.

From my experience, the likes of Tableau, Power BI, Excel, and Google Data Studio stand out as powerful aids for analysts. These tools facilitate the creation of dynamic, interactive dashboards that streamline decision-making processes and foster deeper understanding among stakeholders. Oracle's suite of products complements this by not only integrating with these visualization tools but also providing a platform where data analysis seamlessly transitions into visually compelling representations.

In the art of data storytelling, the first step as a data analyst is identifying our audience, not just by title but by immersing ourselves in their world—gauging their professional background, their incentive for engaging with the analysis, and contextual familiarity with the project. Then, in crafting our narrative, we must meticulously plan and prioritise the visual elements based on time constraints and the nature of our audience. This approach shapes the flow of our insights, determines our starting point, reiterates our objectives, and clarifies the relevance of the KPIs chosen to guide our journey. The insights then become a reflection of our performance and efforts, pointing us towards promising courses of action.

Case stories for learnings aka failures from the project and success stories for far reaching impacts add tremendous value to reporting.

The process of refining KPIs is critical to maintaining their relevance over time and aligning them with evolving strategic objectives. Continuous feedback from stakeholders is essential, ensuring that KPIs remain aligned with user needs and expectations. By benchmarking against industry standards, organizations can not only gauge their performance but also drive improvements that are in line with best practices. Ultimately, the diligent review and update of KPIs serve as a compass, ensuring that data analysis efforts support the dynamic nature of business strategies.