Raoul Harris
  • Introduction
  • Technical books
    • Data engineering with Alteryx
    • Deep learning in Python
    • Generative AI in action
    • Generative deep learning
    • Outlier analysis
    • Understanding deep learning
    • Understanding machine learning: from theory to algorithms (in progress)
    • Review: Deep learning: foundations and concepts
  • Technical courses
    • Advanced SQL Server masterclass for data analytics
    • Building full-stack apps with AI
    • Complete Cursor
    • DataOps methodology
    • DeepLearning.AI short courses
    • Generative AI for software development
      • Introduction to generative AI for software development
      • Team software engineering with AI
      • AI-powered software and system design
    • Generative AI with large language models
    • Generative pre-trained transformers
    • IBM DevOps and software engineering
      • Introduction to agile development and scrum
      • Introduction to cloud computing
      • Introduction to DevOps
    • Machine learning in production
    • Reinforcement learning specialization
      • Fundamentals of reinforcement learning
      • Sample-based learning methods
      • Prediction and control with function approximation
  • Non-technical books
    • Management skills for everyday life (in progress)
  • Non-technical courses
    • Business communication and effective communication specializations
      • Business writing
      • Graphic design
      • Successful presentation
      • Giving helpful feedback (not started)
      • Communicating effectively in groups (not started)
    • Illinois Tech MBA courses
      • Competitive strategy (in progress)
    • Leading people and teams specialization
      • Inspiring and motivating individuals
      • Managing talent
      • Influencing people
      • Leading teams
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On this page
  • Designing your team for excellence
  • Main topics
  • Selected notes
  • Structuring your team for excellence
  • Main topics
  • Selected notes
  • Managing team dynamics
  • Main topics
  • Selected notes
  • Creating sustainable team performance and learning
  • Main topics
  • Selected notes
  1. Non-technical courses
  2. Leading people and teams specialization

Leading teams

Designing your team for excellence

Main topics

  • Team size

  • Surface-level vs. deep-level diversity (observable vs. non-observable characteristics)

  • Personality and team performance

  • Person-team fit

  • Team goals

Selected notes

Larger teams tend to be more innovative. (Hülsheger, U. R., Anderson, N., & Salgado, J. F. (2009). Team-level predictors of innovation at work: a comprehensive meta-analysis spanning three decades of research. Journal of Applied Psychology, 94(5), 1128.)

Founding team size also seems to predict tech-startup growth and board size is positively related to performance.

There's some research suggesting that team satisfaction is maximized at around four or five members, but that is different from maximizing performance, which (according to the course) tends to peak somewhere between five and ten in most cases.

Age (weakly) and tenure negatively predict team innovation, while education and variance in functional background are positive predictors.

Demographic faultlines (where there are subgroups based on the co-occurrence of multiple demographic factors) reduce cohesion and increase conflict, though they increase cohesion within the subgroups.

While diversity of skills and background is important, it is also important that employees feel that they fit with both the team and organization in terms of things like values.

Specific learning goals hurt performance on complex tasks by narrowing focus, which reduces teamwork, learning, and innovation.

Difficult goals are beneficial if the team has a learning orientation, but detrimental if they have a performance orientation.

Structuring your team for excellence

Main topics

  • Formal team structures

    • Departmentalization

    • Centralization

    • Rewards

    • Virtual teams

  • Informal team structures

    • Roles

    • Norms

  • Team charters

Selected notes

Specialist team structures (those organized by functional specialities) are best for predictable environments, but generalist structures work best for dynamic environments. Centralized vs. decentralized authority shows the same pattern for execution-focused vs. creative tasks.

It is generally easier to transition from a specialist structure to a generalist one than the other way round. This is because under a specialist structure teams are forced to develop norms for communicating across functional silos.

Centralized authority can work well when there is less team interdependence or high diversity of experience within the team.

Switching between centralized and decentralized authority tends to hurt performance, particularly if it's from decentralized to centralized.

Competitive rewards work well to encourage speed and efficiency. Cooperative rewards are better for encouraging accuracy and quality. The evidence on hybrid rewards is mixed.

Geographic dispersion in a team reduces contextual knowledge and increases coordination costs. I'm reminded of Hamming's distinction between open-door and closed-door engineers.

To combat some of the downsides of virtual teams, you should ensure that clear support structures are in place and that people feel empowered and that it is safe to speak up.

A team charter is a document that outlines the foundational aspects of a team, such as the team's mission, objectives, roles, and operational norms.

Managing team dynamics

Main topics

  • Avoiding coordination traps

  • The common information effect

  • Social loafing

  • Understanding language gaps

  • Managing task and relationship conflict

Selected notes

In teams, we tend to discuss common information the most even though it would be more useful to discuss unique information. This can be countered by fostering norms of debate, framing discussions as problems to be solved rather than decisions to be made, rank ordering alternatives rather than selecting a single best option, making differences in expertise more salient, minimizing status differences, paying attention, and making sure that everyone contributes.

Larger teams encourage social loafing (freeriding/reduction of individual effort). This can be addresses by assigning meaningful tasks and unique roles, making individual contributions identifiable, using hybrid reward structures, and investing in relationship formation. Apparently, moving from one person to eight in a tug-of-war reduces each individual's effort by half.

Be aware that English may not be everyone's first language. This is particularly relevant for meetings.

While relationship conflict is bad, task conflict (disagreements about how best to approach a piece of work) can be beneficial provided that decisions can still be made and morale can be maintained.

Compromising on a single issue is rarely the best approach. It is often possible to bring other issues in to the picture and make trade-offs across the issues. The example given was of two departments that both wanted to hire someone, with the solution being that one got to hire someone but that some of their R&D budget was shifted to the other.

Creating sustainable team performance and learning

Main topics

  • Evaluating team performance

  • Creativity and psychological safety

  • Transactive memory and team learning

Selected notes

Even if a team is objectively performing well, it is important to understand their subjective performance. If people in the team mistakenly feel that it is performing poorly, this can impact morale, hurting performance and retention over time.

When polled, course participants thought that brainstorming in groups would be most effective. In reality, it is much better for each individual to brainstorm separately first.

The evidence from science suggests that business people must be insane to use brainstorming groups.

Furnham, A. (2000). The brainstorming myth. Business strategy review, 11(4), 21-28.

(The course used a different citation, but this one predates it.)

Issues:

  • Production blocking (can't suggest different ideas at the same time)

  • Fear of judgement

  • Anchoring

  • Social loafing

But people come away from brainstorming with the impression that it went well...

A better approach is for everyone to come up with ideas alone, limit discussion to clarifying the ideas and then take a secret rank-order vote.

The importance of psychological safety is obvious, but a lot of teams and managers could do with bearing it in mind.

Training with the rest of the team is particularly useful for developing transactive memory (not just a body of knowledge, but also which team members know which things). This improves coordination and is particularly useful for execution-focused teams.

Sharing workload can increase team learning, but it also increases coordination costs.

Last updated 7 months ago

The Nine Belbin Team Rolesbelbinteamroles
Brainstorming: 3 reasons why everything you know is wrong. - Barking Up The Wrong TreeBarking Up The Wrong Tree
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Poll taken during the course on the brainstorming effectiveness of teams vs. individuals