Well-chosen Key Performance Indicators (KPIs) have the potential to offer businesses great clarity in pursuing their goals, recognizing impediments to performance, and realizing continuous improvement.

Using KPIs, front-line employees can see how well they are contributing. From team to department to division, goal-aligned KPI performance compounds efficiencies at all levels. At the highest strata of the organization, leaders can adjust plans before misconceived projects or initiatives reverberate through the workforce.

Over time, the right KPIs lead to a more engaged, collaborative, and effective business culture.

But it is crucial to be granular in the way you define and apply KPIs. Although they are often spoken of as a monolith, there are various ways to conceive of KPIs, The type of KPI must be precisely suited to the situation.

The Difference Between Quantitative And Qualitative Indicators

At the highest level, you have quantitative indicators and qualitative indicators. All other kinds of KPIs are ultimately understood with regard to these two, which strike to the core of how to best use your available data.

What Are Quantitative Indicators?

The age of Big Data transformation, with the primacy of the data scientist, has been driven by quantitative indicators. Quantitative data can be measured in numbers and is amenable to statistical analysis. To go back to perhaps the grandfather of all modern KPIs, failure rate per 1,000 units manufactured is a quantitative indicator.

Quantitative data is also the realm of the CFO and accurate forecasting of financial performance.

What Are Qualitative Indicators?

By contrast, qualitative data is usually recorded in the form of a narrative response to a relatively open-ended question. It is inaccurate to say that qualitative information cannot be measured, but it does not lend itself to the same mathematical precision of digital age mainstays such as page counts, dwell time, and bounce rate.

Considerations for Using Qualitative Data

Any time you try to apply a quantitative schema on a qualitative data set, your measurements will by necessity be imperfect. However, that does not mean this never happens or that it can never be useful: Net Promoter Score (NPS), one of the most widely used KPIs of all, applies a 1-10 numerical overlay to customer sentiment.

Because of their simplicity and intuitive nature, the 1-10 or 1-5 scales are very often used as the overlay for putting qualitative data into a quantitative framework. For example, in semantic analysis you could rank the word “awesome” among the most positive words to use about a brand (10) and “terrible” among the least (1).

This means, of course, that you must strive to think like the customer (or other target stakeholder group being studied) whenever you categorize and classify qualitative indicators. Failure to do so can skew the results by imposing meaning, such as value judgments, where the original respondents did not intend it.

In recent years, businesses have become more adept at integrating qualitative data into their worldview. Employee satisfaction surveys and customer sentiment analysis on social media are just two of many examples.

That said, when there is a business problem to be solved, decision-makers will often reach for the available quantitative data. This can save time in data processing and research, but leaders must be cautious not to measure the wrong thing simply because it is easy to find. That is one of the hallmarks of a poorly defined KPI.

Though most of your data will be quantitative, recognize that taking the extra steps to gather and process qualitative data is sometimes warranted. Without both types of data, you end up with an incomplete picture.

6 Kinds Of KPIs You Can Use To Reach Your Enterprise Goals

As you delve deeper into the different kinds of KPIs, it becomes easier to see how to develop the right KPIs for given business situations. While there are KPIs with broad applicability within or between fields, remember that time and attention are limited: An individual should rarely be expected to manage more than three KPIs.

At the team level, it may be possible to manage more KPIs, but the risk of focusing on things not directly within the team’s sphere of influence increases with each one. To avoid overreach, KPIs must be selected with precision. These categories will enable you to do so.

Six core types of KPI are:

Leading Indicators

Leading indicators correspond to a future movement or change. The ongoing shift from descriptive to predictive data analytics means more enterprises now have access to leading indicators that pertain to relevant trends in their market. However, this data must be monitored and disseminated to decision-makers effectively.

• Changed buying behavior, online search patterns, and social media discourse can be leading indicators

Lagging Indicators

Lagging indicators consist of information available after the fact that further clarifies the performance of some initiative. Organizations generally capture and evaluate lagging indicators in the form of project post-mortem reports. They serve to confirm trends, but they do not predict them.

• Company revenue is perhaps the most common lagging indicator – it does not predict future results

Input Indicators

Input indicators measure the assets committed to a particular outcome. Resources, time, and personnel earmarked for a project are quantified so they can be adjusted to the optimum levels. It is critical to avoid the fallacy that “bigger is better,” since higher levels of input can suggest process inefficiencies and waste.

• In project management, the project’s actual budget and total people-hours are traditional inputs

Process Indicators

Process indicators describe the attainment of particular processes according to plan. Executing on these basic business processes enables progress toward other goals. Process indicators will vary greatly by context. As indirect indicators, they must be defined carefully to avoid injecting “busywork” into affected workflows.

• In onboarding, distribution of training materials and login credentials may be process indicators

Output Indicators

Output indicators are the results that arise from the execution of business processes, external to the processes themselves. Output indicators are sometimes used as process indicators, although this can introduce some ambiguity into the cause-and-effect relationships being examined.

• In the same employee onboarding above, the employee passing basic skills tests may be the output

Directional Indicators

Directional indicators are evidence that an individual, workgroup, or company is getting better or worse at something. Process-level KPIs held by front-line employees can easily be used as directional indicators to foster growth. KPIs can also be aggregated in cases where individual KPIs are assigned differing weights.

• Time-to-complete calls and first-call resolution could both be used directionally in a call center setting

For a complete view of business performance, leaders must synthesize KPIs correctly:

• Quantitative indicators with qualitative indicators
• Leading indicators with lagging indicators
• Input and process indicators with output indicators

At a fundamental level, KPIs are the informational architecture that enables you to transform inert data into insights that drive human performance. That, in turn, guides the development of a company culture where clarity, sound decision-making, and excellent performance arise as fundamental values.

To learn more, contact Equal Parts today.