A Data-Driven Approach to Managing Skill Sets to Meet Changing Business Needs
People are the key assets of any business. Their skills define what the business can offer to its customers, how it can develop new capabilities, and how it can address problems and opportunities. Since most businesses require a broad set of skills, the business will require a diverse team of people to deliver them. The needs of a business are constantly changing, which means that the skills of the people within the business need to change over time. To address the skills required by the business, leadership needs to identify:
- The current skills possessed by the people
- The skills required by the business
- Skills at risk
- New skills required to grow the business
- An approach to close any gaps
We will present our approach to skill planning, inventory, and staffing. Our approach is data-driven and has the advantage of Intertek Allentown (Pennsylvania) being an independent profit-and-loss unit within the broad Intertek network. The global Intertek Group is a contract services provider in the testing, inspection, and certification market. Intertek Allentown specializes in analytical testing, characterization, and problem solving in the chemicals and materials areas.
Skills analysis is a study of complex and competing needs. It contains both an analysis of the skills currently available and estimates of what new skills need to be developed and what existing skills may be at risk to leave the business. These skill needs also must be addressed with a finite amount of resources, so prioritization is critical.
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Skills analysis involves a series of questions to probe the existing skills and changes to the skill sets required by the business. Examples of these questions include:
- What specific skills do individuals possess now?
- What is the risk of any of these individuals leaving the business?
- Which skills does the business need to increase?
- Which skills can the business afford to decrease?
- Who has the interest and ability to train in additional skills?
- Does the business have capable teachers to complete internal training?
- What is the performance level of the current staff ?
Fortunately, data are available to help address many of these questions. Good sources of data about existing skills of the employees can be found in both human resources (HR) and quality management system (QMS) files. Both HR and QMS may have copies of resumes or CVs that will include degrees and previous work experience that show different kinds of skills in employees. Laboratory information management systems can provide information about the current activities of both individuals and laboratories to see the existing demand on the staff and provide information about trends to help with estimates about future skills needs. Sales and revenue data (for a stand-alone business) or budget data (for an internal department) can provide indications of the value of the skills to the various customer groups. Together, these data can be analyzed to build a more informed image of the existing skills and the future demands on the staff skill sets.
For our internal skills analysis process, we complete the following sets of analyses across our internal laboratories:
- Skill level distribution
- Age distribution
- Skill risk
- Workload distribution
- Profitability distribution
Figure 1 shows our skill level analysis across all our internal laboratories at Intertek Allentown. We have three different skill levels in our laboratories:
- Subject matter experts (SMEs)—local and world experts in their area; key problem solvers responsible for developing new methods and capabilities
- Practitioners—solid, midlevel contributors who modify methods, analyze data, write customer reports, and address customer inquiries
- Operators—junior scientists and technicians who are responsible for keeping the instruments operating properly and creating high-quality data
Typically, our skill level distribution is around one-third in each category. Right now, we have a little over one-third (40 percent) as SMEs and a little less than one-third (27 percent) as operators. By analyzing these data, we can see opportunities for improvement. For example, three different labs—BT, HP, and OM— have no operator support. Each of these labs still has technician-level work to be accomplished. Part of our team development plan for 2016 is to develop partial full-time equivalents of technical support to enable the more experienced scientists to work to their skill levels more often.
Like many businesses, we developed an imbalance in the age distribution over time. Having too much knowledge in a single cohort who all may leave in a narrow time window, the business carried too much risk of losing critical knowledge. Through significant hiring in the 1980s and limited hiring through 2010, we developed a staff that had a significant majority with ages above fifty. Since 2010, our business has grown, and we’ve had the opportunity to do some hiring. Between the new hiring and some retirements, we’ve been able to gain more balance in our age distribution, reducing our percentage of staff over fifty from two-thirds to almost one-third.
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Our current age distribution analysis still shows some opportunities to improve. We still have two laboratories that have nearly all the staff aged over fifty. One of these labs has a consistently growing customer load. That lab will need additional cross-training of some younger staff in 2016 to share critical knowledge. The other lab has a consistently declining customer load. With limited resources, the skill risk posed by the aging staff in this lab will simply be acknowledged in 2016.
The best way we have found to address skill risk is the prioritization tool developed by the Tennessee Valley Authority.1 Our approach to skill risk and prioritization was previously described in Lab Manager in an article on knowledge retention and transfer.2 In our current skill risk analysis, we have identified four labs with critical knowledge that may become a risk in the three-to-five-year time period. We are now including cross-training and succession planning, starting in 2016, to start to address these risks.
Figure 2 shows the workload analysis across all our internal laboratories. The workload is normalized for the HC lab, which has the highest lab workload. The workload analysis can be very beneficial to our prioritization process for skill planning and skill building. We want to further invest with new people, additional training, and new equipment in the labs where we get the greatest benefit. For Intertek Allentown, the greatest benefit can be seen as the labs with the highest workloads for our customers. Figure 2 shows a wide diversity of workload levels across our internal laboratories. Three labs—HC, HW, and OM—have significantly higher workloads than the others, and we are including additional training plans in 2016 for these laboratories.
The workload analysis can be augmented with additional information, including normalizing to the number and skill level of staff in the labs and the profitability of the labs. As a business, we are concerned with both the workload, or the quantity of the business, and the profitability, or the quality of the business. By including these additional data in our analysis, we can more easily identify the best and most important labs in which to invest.
Figure 3 provides a summary of the workload and profitability data across our individual labs. The columns identify impact, which is a measure of the current contribution to the business from each lab. The rows identify potential, or our estimates (based on trend data) of future contributions to the business. Our 2016 skills plan will focus on labs that have medium and high impact with high potential. Despite some skills needs, labs with low potential are unlikely to be key participants in the 2016 skills plan.
At Intertek Allentown, we take a three-pronged approach to skill building:
- Performance management
- Cross-training plans
- New hires
Performance management is a critical process. We need to clearly understand who the high performers are and work carefully to involve them in new skill-building opportunities to ensure they reach their potential. To ensure we have effective performance reviews, we have a simple process:
- Interim review halfway through the year—We provide clarity on objectives and expectations and have the opportunity to provide direction and guidance.
- A one-page performance review that highlights accomplishments and key opportunities for improvement.
- A clear conversation at the annual performance review—The conversation is far more important than the written document.
- Annual objectives that have contributions from both the employees and leaders and focus on accomplishments, not activities.
- We focus on growing strengths:
- We hire people due to their strengths.
- People develop strengths from a combination of interest and ability.
- Growing strengths can lead to excellence, while growing weaknesses can, at best, yield mediocrity.
- We focus on a weakness only if that weakness prevents the employee from finding success.
Performance management also is critical to either reshaping or removing poorly performing staff. We want to spend our time and resources improving the skills of the good and high performers, not extending the tenure of poor performers.
Cross-training plans are first built strategically for the business. They are the output of the skills analysis. The overall cross-training plan is directed at specific individuals to accomplish specific goals. Individual cross-training plans need to include:
- Specific scope
- Time expectations
- Depth of knowledge expectations
- Mode of training (internal or external)
- Metrics to identify success
Individual cross-training plans are included in an employee’s annual objectives, and if the training is done internally, also included in the teacher’s objectives. We have a variety of cross-training tools that have been used successfully in our business. They focus on the mode of information to transfer either tacit knowledge or concrete knowledge. The tools were previously described in Reference 2.
By developing and using a defined skills analysis process, we have improved our organization and enabled our business to grow. By using the lab and business data available, we have been able to make data-directed decisions to optimize scarce resources. Our performance review and cross-training processes have enabled us to shift skills to meet new business opportunities. The outcomes have included key improvements:
- More balanced age distribution across the labs • More balanced skill level distribution across the labs
- Effective metrics for business impact and growth potential
- Effective cross-training process
- Strong and flexible lab staff
1. Critical knowledge grid shared by the Tennessee Valley Authority during a KRT sharing event sponsored by APQC.
2. Hanton, Scott, “Retaining Business Critical Knowledge,” Lab Manager, November 2013, 28.