Designing and Tracking Knowledge Management Metrics

Alexeis Garcia-Perez, Farah Gheriss, Denise Bedford

• Publisher: Emerald Publishing Limited
• Year: 2019
• ISBN:
  9781789737257
• Topic: Betriebswirtschaft
• Subtopic: Informationsmanagement

Knowledge management metrics are one of the weakest areas of practice in the field. Overwhelmingly, the literature that exists focuses on case studies and incidents of metrics, rather than approaching the concept holistically.
Addressing this lack, expert authors Alexeis Garcia-Perez, Farah Gheriss and Denise Bedford come together to supply a fundamental discussion of measurement cultures and philosophy, types of metrics, and how to use metrics to grow an organization. They offer a guide for knowledge management professionals to report on progress against goals and targets in terms that are understandable and comparable to their organizational peers, enabling professionals from across businesses to communicate with metrics and engage in wider discussion about the process of achieving organizational visions.
Providing practical guidance for identifying different types of measurements and metrics, as well as methods for defining and collection information about metrics, this is an essential book for knowledge management professionals and researchers on the path to improving metric literacy across their organizations.

SECTION 1

METRICS AS A DECISION-MAKING TOOL

1

METRICS IN BUSINESS AND KNOWLEDGE MANAGEMENT

CHAPTER SUMMARY

This chapter provides a definition and characterization of metrics, and explains the value of metrics as a management tool for reducing uncertainty and managing risk. The authors provide some fundamental assumptions about metrics and explain how metrics relate to measurement. The chapter identifies common business metrics. The current state of knowledge management metrics is discussed. The authors make the case for aligning knowledge management metrics with business metrics. Caution is encouraged against using metrics defined by other organizations or developed for different business environments. Each organization must define and develop their own knowledge management metrics.

METRICS – DEFINITION AND CHARACTERIZATION

Metrics are measures that help us to assess, compare, and track something – often performance, production or progress against our goals and objectives (Lavorgna, Turavil, & Metz, 2002). Metrics should be selected based on the nature of the business environment, business goals, and the economic sector in which the organization operates. We are all familiar with the adage from Peter Drucker, the noted management guru and the father of business metrics – If you can’t measure it, you can’t manage it (Drucker, 2012). Metrics are meaningful measurements and calculations that are used to direct and control an organization. Metrics are commonly used to manage business functions, strategy implementation, processes, programs, projects, initiatives, infrastructure, facilities, and technologies – in short, every aspect of an organization’s business and operation. Most importantly, though, metrics are critical tools for decision-making at any level and at every point in the functioning of an organization. Wherever an executive, a manager, or a production supervisor makes a decision, analyzes, and chooses among alternatives, metrics are in play. Decision makers use metrics in a context. Decision-making assumes we have choices, and that we are evaluating those choices in the context of achieving business goals and objectives.

Executives use metrics to analyze corporate finance and operational strategies. Analysts use them to form opinions and investment recommendations. Portfolio managers use metrics to guide their investing portfolios. Furthermore, project managers also find them essential in leading and managing strategic projects of all kinds. Every business executive, analyst, portfolio manager, and the project manager has a range of data sources available to them for building and structuring their own metric analysis. This can potentially make it difficult to choose the best metrics needed for important assessments and evaluations. Organizations require performance metrics to monitor progress against goals and evaluate the effectiveness and efficiency of business processes. Organizations use workload measures when allocating and managing resources. Metrics enhance program processes, boost credibility and can inform decisions about program budgets, priorities, staffing, and program activities. They are also essential for identifying weakness, threats, and deficiencies. In 2019, metrics are often tailored to suit a business and operationalized in the form of a dashboard.

Metrics have been used in accounting, operations, and performance analysis throughout history. Metrics come in a wide range of varieties with industry standards and proprietary models often governing their use. Best practices across industries have created a common set of comprehensive metrics used in ongoing evaluations. However, individual cases and scenarios typically guide the choice of metrics used.

ANALYTICS, METRICS, AND DECISION MODELS

Business metrics have evolved over many decades. The earliest management metrics aligned with financial management and engineering indicators. Over the decades they have grown more sophisticated, more custom-designed for specific business contexts, increasingly automated, and more systematically managed.

There are a number of terms that are used synonymously with metrics, including benchmarks, analytics, dashboards, measures, standards, key performance indicators (KPIs), competitive and business intelligence, and data sciences (Fig. 1.1). While there are logical relationships to each of these terms, they are not equivalents to metrics. All metrics leverage measures and measurement but not all measures are metrics. Metrics may be promoted as a standard, but not all metrics are standards. Metrics are displayed in dashboards but not all metrics are or need be automated or machine based. Metrics that are specific to an industry, an economic sector or a function may be designated as a KPI. Competitive and business intelligence methods all refer to and produce metrics of some form. Finally, data sciences focus on computational methods that may or may not generate a metric.

Fig. 1.1. Common Synonyms Related to Metrics.

METRICS IN CONTEXT

Metrics are always used in the context of making a decision. Metrics play a critical role in decision-making – whether formal or informal – they represent what factors you take into consideration, what evidence you use and how you analyze that evidence. We decide which metric to use based on our understanding of the decision and all the factors that affect the decision. Metrics can also help us to determine whether the way we’re making decisions is optimal or suboptimal – by analyzing the use of metrics you can understand where and how you might improve your decision-making processes. One of the challenges we face is that metrics are often discussed “out of context.” This is a challenge in the field of business, where we have robust definitions and characterizations of decision-making.

COMMON ASSUMPTIONS ABOUT METRICS

We offer five basic assumptions as a foundation for understanding metrics:

(1)Are measurable. Many organizations have established the principle that strategy and performance goals need to be measurable. As such, it is common for metrics to be developed for the purposes of strategic management, goal and performance management. Not all metrics measure goals. For example, metrics can also be used for decision-making, problem solving, and optimization.

(2)May be relevant to core capabilities and critical to business performance. Key performance indicator (KPI) is a term for a metric that is critical to an organization. It is common for organizations, departments and teams to develop a large number of metrics. The term KPI is used to distinguish those metrics that are critical to strategy. In most cases, a KPI is used to measure goals.

(3)May be qualitative or quantitative or a hybrid. Qualitative metrics are metrics that are based on a human judgment such as a rating. For example, customer satisfaction is typically a qualitative metric that results from asking customers to rate their satisfaction with a product, service, or experience. Although qualitative metrics result from complex human judgments, they are typically represented as a single number. Quantitative metrics are a class of metrics that are based on numbers. They can be financial or non-financial in nature. Examples of quantitative inputs to metrics include revenue, customer counts, or electricity usage measured in watts.

(4)May be actionable or simply informational. Actionable metrics can be useful for making decisions and for optimizing work. It is common for organizations to mandate that all metrics be actionable. Informational metrics are metrics that are not intended to be actionable. People find information interesting and may develop metrics that are unlikely to change the course of decisions. This is widely considered a distraction and unnecessary expense. For example, if a car displayed the temperature of its muffler on its dash, some people might find it interesting but this isn’t actionable like a fuel gauge or speedometer. As such, it might be considered an unnecessary distraction. Both informational and actionable metrics are important sources for decision makers.

(5)Vanity metrics are designed to influence an impress an audience but they are often thought not to be useful or practical. No source of evidence should be dismissed without understanding how it might apply to an organization. Given the expanded scope and coverage of knowledge organization metrics, the authors do not dismiss vanity metrics as unimportant.

METRICS AND MEASUREMENT

Metrics and measures are two terms that are often used interchangeably. In fact, they have different definitions and contexts. Knowing the context is important. Metrics are decision-making and management tools. Measures are numbers. Let’s begin with a definition of a measure. A measure is a data point at a single point in time. Measures often answer questions like “how many,” or “how much.” Measures can answer these questions. Measures and measurements are sources of evidence or information related to a business metric. Measures can exist out of context. Metrics must have a context.

A metric is a data point in context. A metric considers the past, the present and the future – and puts your success or failure in context. A metric encourages continual improvement. A metric is an analytical tool that allows you to evaluate and choose among many alternatives in a business situation. Metrics provide a context for understanding the differences in alternatives, the change in performance, a trend over time, or sources of growth and improvement. Metrics require a measurement baseline. If you are using measures to make decisions, the chances are high that you are not identifying and comparing alternatives but simply learning about “what is.”

WHY WE CARE ABOUT METRICS

We care about metrics in business because they are critical management tools. We care about metrics in knowledge management for the same reason – because they are essential to managing knowledge management functions and capabilities, to managing the use of knowledge in business processes, and to manage...

Table of contents

• Cover
• Title
• Section 1: Metrics as a Decision-Making Tool
• Section 2: Building the Organization’s Capacity for Knowledge Management Metrics
• Section 3: Measurement Methods and Sources
• Section 4: Implementing the Measurement Strategy
• Appendix: Developing a Knowledge Metrics Strategy – A Project Plan
• Index