How do you set KPIs for your BI strategy?

The approach I've used in the past is before you get down to brass tacks with metrics you need to understand the business questions the different functions are asking themselves. Two types of questions; performance questions (what happened today and yesterday) and analytics questions (what might happen tomorrow or in the future etc.). You can then align these with the metrics, but the main aspect here is to drive it through business questions linked to the overall strategic objectives. I created by data strategy canvas which is driven by this perspective.

It is important to select KPIs that supports "value creation" by aligning them to the business strategy. It is also important to have KPIs that are SMART (Specific, Measurable, Attainable, Relevant, and Time-Bound), in addition to KPIs that undergo "predictive analysis" and retrieve values for the next 6 months or 1 year. Moreover, OKRs (Objectives and Key Results) can be the agile form of KPIs, that can be measured more frequently, for the business.

1. Aligning KPIs with business objectives is pivotal. Take retail, for instance. When our goal is to boost revenue, we focus on BI-driven KPIs like tracking conversion rates and average transaction values. 2. We must also consider strategic harmony. In healthcare, improving patient outcomes leads us to BI KPIs centered around reducing readmission rates and enhancing treatment adherence. 3. Moreover, high-level goals guide our KPI choices. Consider e-commerce: for an improved user experience, we base BI KPIs on measuring website bounce rates and user engagement metrics.

Strategy I found helpful: - To find out who is the targeted audience for the KPIs? These could be vary depending upon the functional area. For example KPIs for a finance manager may be very different than an operations manager at a manufacturing firm. Having a clear sense who is to measure what is key before beginning work to create KPIs.

Kpi's,should be define by S.M.A.R.T inicials : S -specific M - mesurable A - actionable R - relevat to companirs goals T - timely bound

Main BI project metrics in my experience: 1. User Engagement % as Number of active users / Total number of users within the target audience of the report who is expected to use it * 100%. 2. Satisfaction Metrics like ~ CSAT / NPS with some simplification. 3. Number of active users per period (MAU, WAU, DAU) as a main operational metric. It also can be used with weightening by user / user groups ranks (level in org hierarchy?). Other metrics: - % of reports exceeding the specified threshold for performance speed; - Number of views of Certified content in relation to the total number of views; - Retention -?conversion into second view of the report; - % reports connected to certified data sources; - Average report life duration in days. etc

In today's value-driven data era, setting KPIs for BI strategy isn't just about metrics; it's about vision. Drawing strategies and insights from 'Value Driven Data', it is clear that true value really emerges not just from data but from a clear vision of what we aim to achieve. But how often do we get lost in the technicalities, forgetting the 'why' behind our data endeavours? As we set KPIs, let's shift our focus from mere numbers to the broader vision of creating really tangible economic opportunities and driving beneficial actions. Remember, data is not just the new oil; it really is the new compass that directs our business strategies. So, are your KPIs aligned with your data vision?

1. Direct reflection of BI impact is essential in KPIs. In hospitality, elevating guest satisfaction leads us to BI KPIs centered on monitoring online reviews and guest feedback scores. 2. We must also set achievable targets. Manufacturing, for instance, seeks optimized production processes, so BI KPIs involve measuring production cycle times and defect rates. 3. Furthermore, our KPI selection should align with available resources. In logistics, for efficient supply chains, BI KPIs could revolve around tracking delivery lead times and order fulfillment accuracy.

One helpful way is to split your lead and lag measures. Lag being metrics used to measure past performance ex. return on investment and revenue growth. Lead being metrics used a predictive of future performance ex. add more products to the portfolio this year.

"Framing Business Problems: slicing and dicing" This process starts with comprehending the diverse scopes of organizational and departmental objectives. Subsequently, it involves identifying the core drivers (or) root cause of the business problem, with the help of involved stakeholders. This encompasses empathizing with teams and their challenges, ultimately leading to the discovery of impactful insights and disaggregated approaches to problem-solving. Framing business problems is the linchpin that enables organizations to harness the full potential of their data-driven strategies. (I have seen many newcomers, eager to impress, hastily showcase their skills, overlooking the importance of truly understanding the business problem)

1. Specificity drives effective KPIs. Education, for example, focuses on improving student performance with BI KPIs measuring grade improvements and exam score enhancements. 2. We must also quantify success comprehensively. In the tech sector, enhancing software quality calls for BI KPIs measuring bug reduction, alongside increased user satisfaction ratings. 3. Moreover, consistent units ensure meaningful measurement. Telecommunications, for instance, targeting customer loyalty, relies on BI KPIs tracking customer churn rates and lifetime value in monetary terms.

A good way to define the KPI'S and Key Metrics is that you need to understand the stakeholders/business needs by answer the 5 W's (what, where, when, why, who). It'll help you in mapping out that you actually need, which can later be used for decision making.

Lead vs lag measures could be applied to this portion of the article as well if not applicable above. This way of splitting KPIs, objectives etc. in large companies is a proven way to get employees to focus on what can be influenced by them.

Selecting right metrics is an art as much as it is a science. It's not about collecting data for data's sake; it's about pinpointing WHAT matter most to your org's objectives. Relevance is crucial. Metrics should directly align with the goals and objectives of the org. They should answer questions that matter, shedding light on what's essential for your business's success. Measurability is equally vital; metrics must be quantifiable and capable of providing clear, interpretable results. But it doesn't end there. Metrics must also align with data availability and reliability. You can't rely on metrics that you can't measure, and unreliable data can lead to skewed insights.

The need for continuous monitoring of KPIs (as the data volume grows) is critical in achieving the desired business goals. Two types of KPI monitoring are very essential in modern day BIs. ? Continuous Assessment - Assessing the KPIs based on the benchmark/goal defined. The continuous assessment not only checks if the KPIs’ goals are met but also helps in adjusting/re-aligning the goals. The more important thing is, to make those KPIs actionable for the biz-ops. ? Thoughtful Adaptation - whether the defined KPI itself is pragmatically adapting to the changing business need. The indicators, at times, do not render to the changing business requirements and would need to undergo a complete overhaul. BIs should be proactive instead of reactive.

1. Consistent KPI tracking maintains progress visibility. Finance, for optimizing investment portfolios, utilizes BI KPIs monitoring portfolio returns and risk-adjusted performance metrics. 2. We must also employ visual aids for effective communication. Marketing, aiming to enhance brand reach, utilizes BI-driven KPIs visually displaying social media engagement metrics and website traffic sources. 3. Furthermore, stakeholder engagement fosters collective understanding. Non-profits, for community impact measurement, use BI KPIs sharing data on volunteers' contributions and beneficiaries reached.

BI is all about near-real-time rapid monitoring, insights are most effective when they make an impact right now. Therefore, the people who use the reporting tools wants to make sure they are practical and efficient. Again, a big part of BI is creating dashboards that provide users with clear snapshots of the current state. These tools must be impactful and easy to interpret. Even for non-technical people. Data literacy and maturity -- the extent to which an organization is able to effectively use its data in order to extract actionable insights -- play a vital role in communicating this metrics.

A very key aspect of measuring business performance is creating KPIs from clean and verified data sources. Applying quality control, thus the whole organization views one version of the truth and not siloed data sources producing various reports circulating around.

How do you measure success of your BI/Analytics/Data Strategy? With the pace of innovation in the BI and data space + the constant onslaught of demand for our services it is easy to lose sight of the value proposition. I have seen teams fall into this trap over and over again. Trust me your stakeholders only care about what your strategy and deliver for them. So our KPIs need to align with business outcome expectations. Yes, let's track how many users we are onboarding and how many dashboards/reports are being published/refreshed but let's also track how many decisions are they driving and ultimately what $$$ impact these decisions are generating.

1. Nurturing a culture of continuous improvement is vital. In technology startups, staying innovative requires BI KPIs measuring speed of product feature releases and user adoption rates. 2. We must also integrate feedback loops. Hospitality, for instance, benefits from guest feedback data refining BI KPIs to better align with evolving customer preferences. 3. Moreover, adapting KPIs to changing circumstances is crucial. In the automotive industry, for example, BI KPIs must adjust based on market shifts, focusing on factors like consumer preferences and environmental regulations based on market shifts, focusing on factors like consumer preferences and environmental regulations.

I would like to reiterate on the importance of data cleansing as a non-negotiable step 1 before creating any reports and dashboards based on them. In my experience I have seen a lot of wasted efforts in backtracking a "broken" or "wrong" dashboard or report, which if enough time is spent in scoping first what is the requirement? Is the data verified and ready to be used? Answering these questions is key.

Framing Business Problems This process starts with comprehending the diverse scopes of organizational and departmental objectives. Subsequently, it involves identifying the core drivers (or) root cause of the business problem, with the help of involved stakeholders. This encompasses empathizing with teams and their challenges, ultimately leading to the discovery of impactful insights and disaggregated approaches to problem-solving. Framing business problems organizations to harness the full potential of their data-driven strategies. (I have seen many newcomers, eager to impress, hastily showcase their skills, overlooking the importance of truly understanding the business problem)

From the business’ goals is derivated the BI strategy. The KPI are then set to measure the progress on achieving this strategy. If my company’s goal is targeting a reduction in supply chain cost, my BI strategy will focus on providing better KPI for the supply chain teams. I may setup kPIs to highlight cost saving realised with decisions based on data provided or cost avoidance based on a transportation cost KPIs being kept under control through recurrent reporting.