Founder and Managing Principal of DBP Institute. I help companies transform technology and data into a valuable business asset.
Analytics, at its core, is leveraging data for measuring and improving business outcomes.
Management guru Peter Drucker once said, “What gets measured gets managed.” Basically, effectively measuring business outcomes can help enterprises grow their revenue, reduce costs (direct and indirect) and mitigate risks.
But measuring the business outcomes with data and analytics (D&A) is difficult, complex and time-consuming. In this article, we define the 5P of D&A measurement, i.e., purpose, plan, process, people and performance. These rules can help enterprises in measuring business outcomes in a reliable manner, avoid some of the common mistakes and achieve better business outcomes.
1. Purpose: Only a few entities are worth measuring.
Measurement drives behavior, results and an organization’s culture. It can also help improve accountability, decision-making, employee motivation and resource allocation. Because measuring business outcomes using D&A is expensive, time-consuming and resource-intensive, measurement methodology can vary widely. Basically, only a few things are worth measuring.
Albert Einstein said, “Not everything that can be counted counts, and not everything that counts can be counted.” So, what should businesses measure? Effective performance measurement with D&A should directly or indirectly measure three things: revenue, costs (direct and indirect) and risks. KPIs can be used to track performance against internal goals, industry standards or even competitors.
2. Plan: Measurement should be based on transactional data.
Organizations can use several measurement frameworks, such as balanced scorecards and goal-question-metric (GQM) for planning the measurement initiatives. All these frameworks depend on defining the metrics and the right kind of data to calculate those metrics. In this backdrop, there are three main types of business data: reference data, master data, and transactional data, all three of which I’ve defined in a previous article. Planning for measurement with D&A should be based on transactional data for three key reasons:
1. Every business is an evolving and dynamic entity. Transactional data is not only dynamic in nature but also large in volume. It also records financial value as it deals with the consumption of business resources such as money, time, materials, plants and more.
2. Transactional data fosters relationships between the counterparties (i.e., the participating entities in the transaction).
3. It has a two-fold effect on accounting. This means every transaction hits two or more individual general-ledger accounts.
3. Process: The measurement process should be consistent.
Errors from the measurement process can be random or systematic. Random errors occur due to chance and are uncontrolled. Systematic errors occur when the measurement process is flawed, and these kinds of errors can be addressed.
To address systematic errors, measurement processes should follow the same standards, control the measurement conditions, use tools that are regularly calibrated and follow well-defined criteria during each measurement exercise or period. Even though every measurement process is contextual in nature and driven by time, location and more, the measurement process should be free of any personal opinions or biases.
Following a good measurement process will not only ensure consistent and reliable measurements, but it will also also foster comparability between different measurement periods, entities and categories. Overall, the outcome of a good measurement process is quality data.
So, what is quality data from a measurement perspective? Quality data is the measurement pertaining to operations and compliance that will help the firm grow revenue, reduce costs and mitigate risks. In addition, the data should be governed for security and privacy, and the measurement data should be validated and verified by triangulating the data with multiple data sources. For example, the prices in the invoice should be triangulated with data from the purchase order.
4. People: Every business initiative is a change initiative.
Every business initiative is a change initiative and change can be effective if it is tailored to meet the needs of the people or stakeholders such as employees, customers, vendors, investors, regulators and more.
However, the insights derived from D&A are consumed in dashboards and reports. This consumption is based on the needs of the stakeholder as defined in the MAD (monitor-aggregate-detail) framework. The monitor type of insight offers a quick snapshot of the insights with KPIs and is usually consumed by the senior management. The aggregate type of insight provides information based on pre-defined categories such as customer account groups, geographies, time periods and payment terms. These insights are typically the needs of middle management. The detailed type of insights provides the most granular insights—the lowest level of insights that are of interest to analysts.
5. Performance: Validate the overall measurement engagement.
Measurements provide visibility, and visibility drives performance and, ultimately, business outcomes. Performance measurement helps in objectively assessing the effectiveness and efficiency of the business in increasing revenue, reducing costs and mitigating risks by providing data-driven trends and insights. Moreover, performance measurement can motivate individuals and teams by giving feedback and incentivizing them to improve.
The following five questions will help ensure the validity of the overall performance measurement engagement:
- Why do you want to know?
- How much do you want to know?
- What is the value of knowing and not knowing?
- Who owns the entity that is measured to realize the change?
- Do you have the quality data to derive the insights?
In today’s VUCA (volatility, uncertainty, complexity and ambiguity) world, companies need the ability to manage their performance with greater speed, accuracy and efficiency. Insights hold the key to effective performance management. Conducting measurements and performance improvement with D&A is not a one-time project. If enterprises are looking to stay ahead of the game, they need to continuously measure and improve performance using D&A in a continuous manner.
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