Intel founder and former CEO Andy Grove wrote that, “Measurement against a standard makes you think through WHY the results were what they were.” Business-savvy organizations live by this dictum. They monitor various datapoints and develop key performance indicators (KPIs) – assessable values that show whether a company is meeting its strategic business objectives.
Language services providers and buy-side localization departments benefit from using a variety of business and operational key performance indicators to gain visibility on performance, drive results, shift from reactive to proactive mode, and compensate staff for performance. Business and team leaders recognize the importance of KPIs. However, most LSPs, and even many who work on buy-side teams, have yet to adopt professional data analysis as part of their practices. As a result, many of these organizations don’t benefit from the improvements that could result from better scrutiny of their practices and performance.
During advisory sessions and through survey results, CSA Research has found that many organizations mistakenly label certain datapoints and outcomes that they monitor as KPIs, although those elements do not by themselves demonstrate success in reaching key business objectives. Every KPI is a metric, but not every metric is a KPI. Likewise, not every measure is a metric.

• A measure is a datapoint you track, typically about an individual task, such as the invoice amount per project. Such a measure doesn’t have a goal associated with it. 


• A metric represents the performance of a measure against a corporate goal and often focuses on a process and its audience. For example, one metric is a company’s total monthly revenue versus its forecasted revenue. 


• A key performance indicator belongs to a subgroup of metrics that are strategic in nature, such as the percentage of the sales target achieved or net promoter score (NPS). KPIs sit at the intersection of strategic and tactical focus, and they help you monitor how operational outcomes affect business outcomes.

Many organizations assign random targets and superficially manage their operations with an assortment of metrics that they develop over time based on gut feelings or as reactions to business challenges. Rather than take this ad hoc approach, CSA Research recommends that you systematize your measurement efforts with formal data control and analysis. The following three actions will advance your data analysis:

1. Improve your selection of metrics. Just because you can measure something doesn’t mean that you should associate a goal with it. Focus on datapoints that help you improve business performance. Good metrics are insightful, understandable, painless to collect, reliable, comprehensive, and indicative of the true state of a process. Don’t promote a measure to a metric if it doesn’t meet these criteria.
2. Implement statistical best practices in your data analysis. Get the help of a statistician and implement run charts (that is, results plotted over time) and control charts (process changes over time) to monitor the performance of your metrics. This systematic observation is necessary to understand the typical variation in the data. It also identifies outliers and thresholds above and below which you need to act to ensure that your organization is stable. 
3. Correlate different metrics to identify cause and effect. Establishing this relationship is important, particularly for localization teams perceived as cost centers that must demonstrate the economic value of their activities to management. Use statistical techniques to validate or refute your hypothesis of whether, for example, adding languages increases revenue for an enterprise.

For more advice and concrete examples on metrics and KPIs, buy-side localization teams should check out “Align Your Localization and Enterprise KPIs,” and language service providers will benefit from reading both “Advanced Metric and KPI use for LSPs” and “Seven Less Common Production Metrics to Track.” If the same issues keep appearing and causing problems, it is time for you to systematize your organization’s approach to performance management. Only then will you understand why your results were what they were – and you can begin to fix the root cause.