I mentioned a difficult learning curve I recently went through in my previous post. This new role requires of me to facilitate conversations between small groups of people across the organisation to make high impact decisions, and, man, what a learning curve that was. Driving consensus within a group of people to make data-driven, unbiased decisions is a skill that everyone needs to learn sooner rather than later in their careers. I caught up with a friend recently and we spoke about mechanisms that are useful in these conversations.
I would like to try summarise some of the tools in my toolkit, and also provide examples to illustrate how they can be used.
Don’t make the decision yourself
There are two ways I have seen leaders facilitate decision making conversations. The first, more common, involves a leader/person with authority asking questions from the group, thinking, making the decision themselves, and (if they remember), informing the group of their decision.
An alternative way of approaching the conversation is for the leader to ask questions from all members of the group in such a way that you frame the input to the decision in a clear manner everyone can follow. The person facilitating the conversation can then use summaries to frame what the group has said in such a way that the outcome decision becomes apparent to everyone. You finally ask everyone in the room for their take, allowing room for people to explain why they made the decision. If you use this mechanism well, you can drive the right decision without voicing an opinion yourself, rather, just by asking the right questions and making the group talk.
A benefit of the latter strategy is that you remove single person bias. A decision is much more robust if eight people hashed it out and converged on the same outcome, than if one person made a high-judgement decision themselves. You also get stronger buy-in from the group to commit to the decision using the latter, because people have a stronger sense of ownership if they were part of the final decision making process. Finally, people are part of the journey, allowing them to understand why a decision was made. It makes it easier for them to commit to the decision even if they had an opposing view initially.
Separate framing how to make the decision from the outcome
Imagine a team who needs to decide what database stack they need to use to build a new product. They have to choose between an open source relational data store, or they can get a license for a proprietary relational data store. There are pros and cons to both – with the proprietary platform you get guaranteed support from the vendor, however, you do lock yourself in for a few years, upgrading is harder and you have to consider the licensing cost. With the open source option you need to either support it yourself, or you need to engage with a company that provides support on that open source platform, which also comes at a cost. This is an ambiguous problem with no clear right answer.
You can frame the considerations in your questions and summary, without making the decision yourself. Imagine gathering a room full of people, and asking the following questions:
“Paul, what are the technical risks to us supporting the open source platform ourselves in house?”
“John, which features do we require from our platform, and do either of the two platforms lack any of these features?”
“Grace, If we need additional support for the open source option, which companies provide this as a service, and how much does it cost?”
“Aamer, How much does the proprietary platform license cost, and how long do we have to commit to this product?”
“Paul, What additional costs are involved if we need to do a version upgrade on the propriety platform?”
“Grace, we have never used this open source platform before. What knowledge would we need to develop in house if we were to adopt this solution?”
At no point is a decision being made, yet the questions are targeted to gather specific information about the choice. In choosing these questions you are framing the dimensions which inform the decision – cost, agility, knowledge, support. You are just framing the benefits and risks of both platforms and allowing all the participants to contribute. If cost is of greater concern than knowledge – you have a strong engineering team adept at learning new technologies fast, but you have limited budget, you can bias towards this by choosing questions to reflect this. You can also weigh more heavily on those trade-offs in your summary, while still allowing the group to make the decision.
Ask questions that force people off the fence
People hate climbing off the fence. People also like fishing for information by asking open ended questions. Imagine our database platform decision above.
A few examples of open ended questions:
“Paul, tell me about the open source platform?”
“Grace, you like the proprietary platform?”
“Aamer, what do you think?”
You are going to hang around for a while having this conversation without driving consensus. What is missing? First, you are opening the door for people to waffle on without direction. You are also not introducing those dimensions along which we need to frame the decision we mentioned earlier. Finally, you are not forcing the person to tie their information back to a benefit or risk that informs the decision to be made.
Compare these examples against the examples of questions above. Let’s ask the following question:
“Paul, what are the technical risks for us supporting the open source platform ourselves in house?”
The answer will allow you to summarise the outcome as follows:
“Can I summarise that there is some knowledge we don’t have about this product, but the product has a widely supported user base and well-frequented forum that we can rely on. The risk of introducing a new product into the team can be mitigated by allocating additional engineering effort towards building labs and generating support playbooks?”
Immediately the group can slot this data point into their mental model framing the decision and the ambiguity here has been resolved.
Ask targeted questions and get people to climb off that fence.
Use those summaries
Miller’s Law states that there is a cognitive limitation to the number of data points a person can retain in short term memory at a point in time. People really suck at recalling a long list of data points during a conversation. If you don’t leave breadcrumbs for people to recall everything that was discussed, their recency bias will kick in really early, and this will skew the decision they lean towards in a conversation like we are describing. To manage this, you need to do two things.
First, after every item of discussion, summarise the take-away in short, concise terms, making it clear how the data point relates to our decision. Put a pin in it, and ensure the summary leaves no ambiguity hanging.
Secondly, make room during the conversation to summarise the big picture so far, framing where the conversation stands.
“To summarise so far, the open source platform can save us xx a year in licencing fees if we are equipped to support it in house. To mitigate the risk of introducing a new technology into the team, we will have to invest in building our knowledge base by allocating x engineer hours, as well as expand the support team with two headcount. This will come at a cost of yy, and will require us to hire n people. Let’s discuss the version upgrade feasibility to see how this affects our decision?”
Remove group dynamic bias – make everyone heard
I was discussing this with my friend a few weeks ago, and he asked me how to facilitate a conversation where you are brokering a decision between a junior who has a lot of knowledge about the problem, and a senior who has a lot of authority to make the decision. Ha!
Let’s talk about a few things that introduce bias in group conversations:
Some people are more vocal in group discussions than othersÂ
- Make room for everyone to talk by asking targeted questions to specific individuals
- Learn how to cut ramblers short without being rude e.g. you can interrupt, apologise, and immediately ask a yes/no question to get them to the point and move on
- Write a short document/email framing the context of the decision to be made before the discussion, allowing people to frame their opinions beforehand
- Allow people to submit written feedback/input before the discussion. Build this into your process
In a room with varying seniority, the senior people’s opinion carries more weight
- Engage participants in the conversation from most junior to most senior. This also eliminates the bias of juniors parroting senior opinions
- Ask questions from juniors intentionally asking them to advocate for the opposite position. That way you open a door for them to disagree without being perceived as insubordinate
One person just won’t budge
- If you have one person getting stuck on a single data point, and won’t budge, ask them to motivate why they feel so strongly, acknowledge their point of view, re-summarise the whole discussion so far, and move on. Trust the democracy of the group to de-bias the final decision
Reduce group think
Highly cohered groups often align early during an ambiguous decision making process – sometimes too early. This can happen in groups with high trust, should their trust co efficiency drown out willingness to rigorously explore alternatives.
Intentionally introduce questions asking people to argue for the opposing view – that way the conversation requires of them to explore alternatives without compromising their allegiance to the group.
Sarah-Marie Nothling 