Is your team viewed as not delivering quality deliverables? Is your team perceived as not delivering to high enough standards? I’m going to offer a few suggestions.
Hi, I’m Peter Nichol, Data Science CIO.
One of the big leadership challenges is managing expectations. A lot of times, we give our teams the benefit of the doubt. We encourage them to produce high-quality artifacts, whether that’s data models, data mining analytics, or project plans from a project and portfolio management perspective. Regardless of the actual results, we assume good intent. We hope that the deliverables our teams produce will either meet or exceed our stakeholders’ expectations. However, sometimes it’s just not possible. We didn’t design in quality. Only one person is accountable for poor quality, and that’s the leader.
I want to introduce the idea of portfolio staff leveling. The purpose behind portfolio staff leveling is to ensure that your team has the ability to meet quality standards. For example, let’s assume your team is perceived as not meeting quality standards. The team might produce low-quality project plans that aren’t detailed enough, or the business requirements aren’t elaborated to the degree required. Regardless, of the issue they aren’t meeting the bar. If this occurs and the team is allocated at 110%, it will be tough to have those resources add extra effort to their work products because they’re already maxed out.
This is where portfolio staffing leveling comes into the mix. Instead of taking every initiative or project at face value and delivering all artifacts or deliverables for that project, use some judgment as to which elements are adding value. Start to consider which artifacts are necessarily based on the size of the work. If the program is a multi-year, multi-million dollar effort, you probably need some due diligence, again, if that project is architecturally significant. You probably do need additional documentation for compliance and audit. Inversely, suppose that project is two or three weeks long. In that case, it’s a weak argument to lean towards creating detailed communication plans or elaborate, complicated architecture documents when the initiatives are not significantly impacting architecture.
When we apply portfolio staff leveling on top of team dynamic and, more specifically, team performance, we see positive results. We must allow for quality to be designed into the process. Ask yourself some questions:
- What is my team allocated to this month?
- Is the team delivering consistently?
- Where are the quality gaps?
- Are the critical resources allocated over 90%
Realize that if you do allocate resources at 100% or greater, these resources will have no additional time to elevate their standards or improve quality. However, if these resources are allocated 80% or 85%, they now have extra time to think, be strategic, and plan their next week or month ahead of time.
Aligning a team to expectations is hard work. The quality level is never where you want it. Delivery always seems to be slowing than planned with more rework. When you feel your team is perceived as not performing, make sure that your team has an allocation that promotes quality.
Often when I’m engaged to correct low-performing teams or evaluating a team missing delivery standards, what I discover is that they’re maxed out. These resources are working 50 or 60 hours a week. It might appear to a new leader there is a complex and underlying mysterious problem. The reality is that the team simply needs time to design quality into the process. As leaders, we need to provide that team time to think and give them time to increase quality.
As you head into this new week, take a look at your team. Take a good hard look. Is your team meeting your expectations? Are they meeting the expectations of your colleagues, of your peers? If the answer is no, first analyze if your team has the time to improve their quality.
Be a more decisive leader and give your team time to bake in quality.
Hi, I’m Peter Nichol, Data Science CIO. Have a great week!