Jim Bergeson famously said, “Data will talk if you're willing to listen to it.”
As we near the end of my operational excellence series, this quote serves as the perfect introduction to my favorite pillar of excellence: quality assurance and business intelligence (BI).
Companies that strive to be operationally excellent focus on leveraging multiple forms of automation. This works to augment traditional transaction monitoring in order to have an accurate assessment of quality.
Those who achieve operational excellence realize that quality is critical to their success. In order to ensure quality, customer experience and data should be the central points of focus in all departments in any organization.
When companies leverage data from all available sources, this empowers them to identify gaps in processes, skill sets, and product offerings. Perhaps most importantly, data works to identify future opportunities and generate proactive problem-solving. The power of data can build operationally excellent companies and increase their longevity.
A key part of this is ensuring that all processes, client requirements, and laws are followed consistently across all departments. This is accomplished by using data gathering methods such as speech, voice, and text analytics as well as transaction monitoring/auditing.
Here are 3 central success metrics operationally excellent companies should leverage:
Percentage Reviewed: This metric is calculated as a percentage of the tickets/transactions that are reviewed versus a targeted amount.
Why it matters: More traditional companies rely on sampling methods to ensure the quality of the products and services. While this can provide statically valid sample sizes, nuanced items can go under the radar. By leveraging technology, companies can increase their sampling rate by 10x. This is a fraction of what it would be if a company used traditional transaction monitoring.
By knowing the percentage of the products reviewed or services provided, companies are able to quickly calculate a margin of error. This enables them to focus on identified opportunities by leveraging human capital in a smarter way.
Error Rate: This metric is calculated as a percentage of error in tickets/transactions.
Why it matters: In sampled environments, this was indicative of a bigger problem. Within a data-enabled environment, sampling is no longer necessary. Instead, error rates highlight holistic issues by analyzing a small subset of all products/services.
This is important because error represents a cost to a company. A case study by Stella Connect found that simple changes on first contact resolution (FCR) can save a company a minimum of $62,500 for every percentage point it is increased. However, this does not take into consideration other areas of CX that error rates impact such as customer churn, legal concerns, and employee retraining.
Standard Deviation: This metric looks at the variation from the current process average.
Why it matters: Standard deviation is a more classical way to look at processes and compliance. This helps companies understand how well forecastable results can be projected. This is important for ensuring that employees are trained to handle more complex issues and establish repeatable and internal procedures. The lower the deviation, the more consistent and reliable a company can be.
Through these metrics, operationally excellent companies realize that BI is not simply about automating reports and reviewing data. Quality assurance and BI are a proactive, in-depth analysis used to understand the root cause of changes in a business. This empowers companies to take corrective action to improve not only the customer experience but also the employee experience.
This concludes my series on operational excellence. Data has shown that operationally excellent companies withstand the test of time and changing markets. When will your company start its journey? Drop me a note, and let’s chat, Ben.Hawkins@taskus.com.