Remember, influences are also known as causes, or root causes. Performance consultants use the term “influence” as it encompasses organizational, environmental, and individual influences that are positive and negative; the term “root cause” tends to connote a negative cause while influence encompasses positive and negative causes of a situation.
Here is an example of a real case of influence hypothesis:
One client’s call center averaged a 20–60 minute call wait time and about 50 percent call abandonment. The business goals were to have calls answered in less than five minutes, with less than 10 percent of calls abandoned. The department manager believed that the primary cause was inadequate staffing for the number of typical customer calls per day. For years they had been unable to uncover the causes and influences, and were not meeting business goals. The data analysis—which included observations, staff and customer interviews, surveys, data review, and process and outcomes mapping—produced significant data.
The data found many contributing influences, categorized into this influence hypothesis.
- General influences (work processes, redundancies, and lack of inputs): The call routing system only sorted calls into English-speaking and Spanish-speaking queues. The inadequate call routing meant that a simple request to change an address might be routed to a very experienced CSR, while a newer CSR might receive a difficult request to deal with a delinquent invoice.
- Workplace/structural influences (working conditions, tools and equipment, distractions, safety, ergonomics, workload, and teamwork): The manager and supervisors did not provide adequate feedback and encouragement linked to the CSR’s call volume/output. The websites for customer services were inadequate; customers who called could not leave a call-back number, which would their place in the call queue. The legacy software used to input and track customer data was extremely difficult to learn and use, so most CSRs only became proficient in its use after a year on the job.
- Learning and development (training access, lack of connection to performance, timing, and access to subject matter experts): Onboarding and training were focused on learning the legacy customer data program, with little practice in a simulated or coaching environment. Once training concluded, new CSRs were placed into the phone queue to answer all types of customer calls, with inadequate mentoring and coaching, and practice in dealing with customers’ issues.
- Talent acquisition (recruiting for specific skills, orientation and support, and compensation and benefits): The agency hired and trained temporary workers instead of recruiting those with a full-time commitment. New CSRs and experienced CSRs were expected to take the same number of calls, regardless of the calls difficulty; there was little structured on-the-job-training and support. New CSRs did not know if they would be retained after their initial year of training and answering calls; turnover was more than 50 percent, leading to a persistent lack of trained staff.
- Managerial and structural support (access to manager, communication, control, reporting structure, performance expectations, and feedback): The manager meant well, but was promoted beyond his capabilities; he did not provide appropriate guidance, performance support, clear expectations, or feedback related to performance. Some staff reported that the manager played favorites and was often unavailable.
- Personal motivation (workload, job meaning, negative consequences, lack of consequences and incentives, level of authority, and variety): Many of the CSRs who were hired through the years did not like the atmosphere of the department, and transferred to another department as soon as an opening was identified; this brain drain left the department in constant recruitment and replacement mode. The work had not been enriched and made engaging with the building of the team esprit de corps.
- Technology (mismatched requirements, challenges, functionality, usability, and effectiveness): The technology was typical of an organization that kept patching a legacy system due to lack of funds. Customers could not manage their own files nor pay through a secure online system; the systems had low usability and needed functionality.
Next, prioritize the influences and begin to match the potential solutions with identified influences.
If you were the performance consultant, how do you think you would prioritize these influences, in preparation for meeting with the business unit manager? What solutions would you match to these influences?
In part 4 of this blog series, we will discuss how you can engage the business unit manager in choosing performance-linked solutions.
In part 5 of this blog series, we will look at implementing performance-linked solutions.
To explore selecting and implementing performance improvement solutions, please join me for the Selecting and Implementing Performance Improvement Solutions (SIPIS) Certificate program beginning on December 1 in New York, New York!