What are the new competencies of leadership in the 21st century? Peter R. Scholtes has written an excellent book on the topic. This book, first published in 1998, seems oddly prescient and largely ignored by many managers still today. Let us dive into Scholte's well-laid-out argument for new competencies needed in organizational leadership and management.
Scholtes details an old set of competencies as a contrast to these new competencies: forcefulness, motivator, decisiveness, willfulness, assertiveness, result- and bottom-line orientation, task orientation, and integrity/diplomacy which detail a management and leadership style popular through most of the 20th century. He makes the point that these old competencies aren't wrong, but more wrong-headed in the context of the challenges we have before us today.
Scholtes then goes on to, inspired by Deming's System of Profound Knowledge, create a new taxonomy for leadership competencies:
- Competency 1 - Ability to think in systems, and how to lead systems
- Competency 2 - Ability to understand variability and manage in relation to it.
- Competency 3 - Understanding how we learn, and leading organizations that can learn.
Coming in Part II of this post:
- Competency 4 - Understanding people and why they behave as they do.
- Competency 5 - Understanding the interdependence and interaction between Competencies 1-4 and how each impacts the other.
- Competency 6 - Giving vision and meaning to organizations.
Let's have a look through each, three in this blog post, and three more next week in Part II. There is a lot to unpack here, Scholtes' book is an excellent place to get started. I plan to unpack and dive deeper into many of these topics in future blog posts as well. If you're not a subscriber, hit subscribe in the lower right and you'll be notified when I release these upcoming blog posts.
🌳Thinking in Systems
Systems thinking is a way of thinking holistically, considering the structures of interactions between constituent parts of a system. There are techniques such as systems dynamics modeling that can help break apart systems into quantitative models, but systems thinking is a general way of thinking about systems both in part and as a complete system together.
We seek to understand a system's "purpose, its interactions, its interdependencies". This is counter to straight analysis which looks at the parts by themselves, divorced from the whole. In systems thinking we seek synthesis, or looking at the parts and the whole. There are strong parallels to how indigenous societies think in this holistic and systemic thinking. Somewhere in Western thought, probably starting with Descarte, we divorced ourselves from the universe and took a deep dive into analysis without a healthy dose of synthesis. That is changing, we are better understanding the value of systems thinking and how we can build muscles for it.
The collective minds of our organizations, and their leaders, often lag, using analysis without synthesis. Systems thinking, and in particular systems dynamic modeling can help to model and better understand emergent complexities within systems. Bringing a systems mindset to your work and team is best done as a team effort, starting small and expanding your understanding of the interacting systems your work operates within.
How does your organization consider the interacting systems of which it is part?
How could you be more intentional about modeling these systems so you can understand inherent limitations and bottlenecks in these systems?
- Leverage Points: Places to Intervene in Systems (pdf) by Donella Meadows
We tend to think most anything that goes wrong is a special cause variation, attributable to a bad decision made by some person in that system. Dr. Deming identified two types of variation in systems, common cause variations, and special cause variations. Common cause variations are those that are built right into the system itself. Without a fundamental understanding of the system at hand, and its types of variation, we can believe we're influencing the system when the "change" we see in data is simply the up/down variation inherent to the variability of the system itself. Perhaps this is the measurement of a delivery time, sometimes early, sometimes late, but stably varying around some mean value.
To truly understand systems, we must have a good sense of the inherent variability that the system itself already has, or we're just chasing randomness when we try to intervene to improve a system. Without understanding intrinsic variation, managers will see problems that do not exist, will miss trends, will attribute problems to individuals who are nearby when the problem takes place, give credit when credit isn't due, will make meaningless future predictions, and not understand the ways a system might be improved. In short not understanding intrinsic variability and variation within a system makes the manager a slave to this variability, unable to see the forest through the trees as it were. This reactive poise can lead to catastrophic consequences. Bottom-line and metric-driven cultures that don't have an understanding of variation can create interesting conundra for themselves.
What does your organization do to consider the variability of metrics and measures you use to make decisions?
How could you start to better understand this for your organization?
- The Improvement Guide: A Practical Approach to Enhancing Organizational Performance (book) by Langley et al.
🎓Understanding how we learn
In today's age, the rates of technological change are staggering. There is always a new tool or system to learn, and without a continuous learning and growth mindset, organizations and people can quickly become left behind. Education has become more of a lifelong journey to explore and grow capabilities and perspectives. There is no longer an ability to go get a comprehensive education and subsequently work your career with that set of knowledge acquired in schooling. We must become meta-cognitive about our learning. We must get better at learning to learn. For organizations that want to build a long-term relationship with a community, this means that they can become a nexus of learning.
Considering what it looks like to have an organizational culture that could be called a learning organization, is an important strategic consideration as well. If your employees feel they can grow their skills, career, perspectives, and capabilities within your organization, and that they have agency and freedom of choice in following their interests, they're more likely to stay with your organization long-term.
We can learn through various means, but to build a learning loop into the process of management, we can think of a new Demming cycle that replaces the PDCA (Plan, Do, Check, Act) cycle. This new learning loop is Plan, Do, Study, Act. We bring the continuous improvement and quality cycle of Kaizen and TQM to our learning. When we do this collectively, with an eye toward systems thinking, variability, and human behaviors, we can truly co-create the learning an organization needs to tackle challenging problem spaces.
Building confidence and capability in how the mind works, and the time it takes for learning to go from knowledge to application are new realities in the modern firm.
Are you meta-cognitive about your own learning?
Do you think about how your organization can position itself to be a learning organization?
What are the important areas for learning in the work you do?
Does your organization make time for people to learn on the job?
➡️ Continue to Part II
If you've enjoyed this article, are looking to build a learning organization, or otherwise grow the resilience and competency of your team, please reach out. I love to hear from you.
I help teams consider their collective capabilities, future visions, and strategies for building impact-driven organizations which can co-create a rich and resilient future. This work starts with understanding your people, how you work today, and what you aspire to, and facilitated conversations toward how you reach your goals for impact and sustainment.