See how Polis and the Crowd Wisdom Project have helped these organisations achieve consensus.
Business: Lawyers/Solicitors in England, UK
Question: What strategy should this law firm take?
The new Board of Directors of a 30-person law firm instructed the Crowd Wisdom Project to survey their staff, in order to obtain the staff’s views on their future strategy. The Board knew that their staff were engaged with the business and therefore wanted an anonymous tool for extracting the best possible wisdom from their team.
The Board knew that it was difficult for colleagues new to any law firm and for junior colleagues, in particular, to make suggestions to the Board. The anonymous nature of Pol.is was therefore attractive due to hierarchical nature of most law firms. Pol.is surveys allow even the newest and most junior member of staff to suggest something, which all other staff members vote on anonymously, empowering all participants.
Spearheaded by the Crowd Wisdom Project, we framed the questions and seeded some simple statements. The Pol.is survey was sent around the staff, via email, by one of the Directors. The staff were encouraged to keep engaging with the process, once the dozens of additional statements were posed.
The law firm were thrilled by the engagement of their team. As our report below reveals, even with only 23 voters, 1531 individual votes were cast in a short time. In total, anonymously the staff submitted 85 comments for their colleagues to anonymously vote upon.
At the Crowd Wisdom Project, we moderated the questions to ensure that nothing inappropriate could be voted upon.
With every statement, the voters had three options: Agree, Disagree or Pass/Unsure. With circa 83 statements, voters needed a few minutes to reply. The staff did not need to sign up to answer the survey, because the way we at the Crowd Wisdom Project deploys Pol.is on an entirely anonymous basis. As is common with websites, Pol.is deposits a cookie on the user’s device to ensure that the user can only vote once.
Deploying advanced statistics and machine-learning, created by the clever people at the Computation Democracy Project, Pol.is discovers groups within groups, based on answers and statements, plotting them on a graph. To each voter, the statements appear in a semi-random order. The more data is collated, the more useful the results. The users do not need to vote on every statement for their votes to count.
To the surprise of the Board, the conversation morphed from one solely about the future strategy of the business, to more granular concerns of the staff. Questions about social events, compressed working hours, Christmas closure and the functionality of their technology all arose, driving further engagement. The Pol.is created a buzz in the business, a pressure valve for anonymously expressing wishes. Evidently, the staff wanted to be heard.
With 1531 votes, the Pol.is report located definitive, previously unknown cohorts/groups within the business. Interestingly, one of the statements created by the staff was a request for quarterly Pol.is surveys.
The Board now have previously unearthed wisdom to consider, which they had not hitherto considered. In addition, the Board are now armed with greater insight as to whether their staff will approve of their decisions. Small easy “wins” were identified, which should improve the efficiency of the business. The survey fostered a collegiate attitude throughout the firm.
Business Client: A mixed occupancy office in Harrogate, England
Question: Covid-19 protocol for the return to the office.
As the occupants of an office returned to their workplace following lockdown, we were instructed by a landlord of a mixed occupancy office to find out what their occupants thought about the threat posed by Covid-19. The landlord wanted to know the various risk tolerances to Covid 19 of the occupants and to collate the very best ideas to keep everyone and comfortable. The landlord wanted to find consensus between the occupants, without inflaming any tensions.
The landlord knew that their occupants varied in their employers, occupations, ages and health risk factors. In addition, members of the public and tradespeople attended the office. The landlord wanted their survey everyone quickly, anonymously and sensitively.
After talking to the landlord, we created the initial Pol.is.
We posed the initial question and then added four initial statements in order to facilitate the conversation. The statement you can see above – “Install CO2 monitors in heavily used rooms to check if ventilation is adequate” – was created by one of the occupants. You will see that the person who created the statement is anonymous.
The Pol.is was open for three days. To distribute the Pol.is, the landlord sent the link to all the occupants.
The landlord gave the Crowd Wisdom Project permission to share their results here. In total, 39 occupants completed the Pol.is. In total, there were 601 votes were cast, with the participants creating 27 additional statements, such as the one above about CO2 monitors. One of the clever parts about Pol.is is that the ordering of the statements is deliberately unpredictable, designed to create a conversation and to find wisdom.
As moderators of the statements, we allowed some statements to be voted on, deleting inappropriate ones. This ensured that the conversation flowed and that nothing untoward was anonymously suggested as a statement to be voted upon.
As you can see, Pol.is cleverly and instantly lines up the questions on a continuum between consensus (on the left) and divisive statements (on the right).
Using advanced statistics and machine learning, Pol.is finds groups within groups, based on answers and statements, plotting them on a graph. The more data is collated, the more useful the results.
Based upon the results, the landlord learned a great deal about their occupants, discovering previously unknown groupings within the office. The landlord then formulated its policies, knowing that the protocols enjoyed consensus approval. In addition, the landlord obtained ideas that it had not previously considered.
The occupants felt engaged with the process, knowing that they had been listened to and pleased to have contributed to their own safety and the collective safety of the occupants.
Media Outlet: Harrogate Informer
Question: What do the people of Harrogate think about the Gateway Scheme?
Harrogate is a town in North Yorkshire, England. In 2021, three of the local councils had used traditional survey tools to ask the residents whether they wanted a £10.9m scheme to change the road layout through the centre of the town. Business groups were largely against the scheme, as was one of the local residents’ groups. Broadly, the cycling groups were in favour of the scheme. This issue became a hotly contested issue, being fought out in the local press.
We worked with the editor of The Harrogate Informer, Tim Cook, to create the polis about the Gateway Scheme. The Harrogate Informer embedded the Polis conversation within one of its news pages.
The below is what the people of Harrogate saw on the news website, but the Polis is now closed. The ordering of the statements is semi-random, designed by Pol.is to generate a healthy, consensual conversation.
Given the massive success of the Polis, with 11,000 votes in several days, the news outlet then launched two further news articles to promote the conversation:
The Gateway poll opened on 18 January, closing at 11:30am on 24 January 2022. During this time, 466 voters voted 23,712 times, with the average voter voting 51 times. In total, voters submitted 223 statements for others to vote upon.
The full results of the poll can be found here.
The results were distributed to the council decision-makers and to local media outlets. Despite the issue being politically fraught, our data scientist found several areas of consensus. Moderation proved reasonably easy. Although the issue was rather toxic, the tone of the statements generated was calm and sophisticated.
Community Organisation: Harrogate and District Law Society
Question: How this prestigious, century-old society of lawyers should work post-Covid
Like many community-type organisations, the Harrogate and District Law Society, which was formed at the end of World War One, had faced a significant disruption to their operations because of the Covid pandemic. With their lawyer membership primarily still working from home by November 2021, the President requested the assistance from the Crowd Wisdom Project. The President wanted to discover what the membership, of circa 100 lawyers, wanted from this prestigious society.
With all in-person events having been cancelled for nearly two years, this made it difficult for the lawyer members to interact, particularly with so many lawyers suffering from Zoom-fatigue.
Assisted by the Crowd Wisdom Project, the President of the Law Society seeded half of the statements, with ourselves suggesting the other half. We provided the moderation of the comments. The Pol.is survey was sent to the lawyer membership by email, by the President. The President’s email, containing the survey, also contained other information and attachments.
The below is what the page which the lawyers were sent via the link embedded in the President’s email. The ordering of the statement is semi-random, designed by Pol.is to generate a healthy, consensual conversation.
Above, you will see that the person who created the statement regarding the annual President’s Drinks is anonymous. In the same box, on the top right, the number of remaining statements to vote on is made clear. Voters do not need to answer all the questions for their votes to count.
Voters have three options: Agree, Disagree or Pass/Unsure. With so few questions, voters needed only one minute to quickly reply. There is no need to sign up to answer the survey, because the way we at the Crowd Wisdom Project is to deploy Pol.is anonymously. Pol.is deposits a cookie on the user’s device to ensure that the user can only vote once.
The Pol.is was open for one week. To distribute the Pol.is, the President sent the link to all members, totalling circa 100.
Deploying advanced statistics and machine learning created by the clever people at the Computation Democracy Project, Pol.is finds groups within groups, based on answers and statements, plotting them on a graph. The statements appear in a semi-random order. The more data is collated, the more useful the results.
This survey only received circa 10% take up. We do not have permission to share the results. The ideas shared by the lawyers will inform the President’s future plans for this historic esteemed Law Society. The fact that the membership was asked for their views was in itself regarded as an intrinsic good.
Community Organisation: a religious organisation in Harrogate, England
Issue: How to run their library post-lockdown
With libraries closed due to the Covid-19 pandemic, we were asked by a religious organisation, whose congregations were not meeting in person, to help them to find the best ideas and to discover consensus, regarding the usage of their library. The pandemic had already brought rapid technological developments for this religious group, some of which were popular and some less so.
This religious organisation did not have a clergy; instead, they made their own decisions, without a hierarchy. Decision-making was often not a quick process, though it was usually thorough, the will of their congregation. Making decisions in an exclusively online world was a new phenomenon, and often unsatisfactory one.
The library committee was aware that traditional online survey tools did not usually generate wisdom in a conversational way, often leading the participants in the particular direction as set by the question-setters. In this instance, what was needed was a genuinely open and transparent wisdom-gathering tool. Pol.is fitted the task.
Working with the library committee, we framed the Pol.is conversation and then created some statements, to commence the conversational flow.
The Pol.is was open for three weeks. To distribute the Pol.is, the religious organisation sent the link to all their congregation by email in their newsletter and by text message.
Using advanced statistics and machine learning, Pol.is found groups within groups of this congregation, based on answers and statements, and plotting them on a graph. The more data is collated, the more useful the results.
Based upon the results, the committee learned a great deal about their congregation and their preferences. With only 20 participants, 427 votes were still cast, with 31 additional statements submitted by the congregation. The 31 additional statements were of great importance to the library committee, with the congregation voting on them.
The library committee discovered ideas that they had not previously countenanced. After analysing the data, the committee formulated new policies, knowing that these policies enjoyed consensus within the congregation and that fresh ideas had been unearthed.
Essentially, each member of the congregation was treated equally and anonymously, although Pol/is does rely on recipients having access to the internet.
The committee distributed the full results of the Pol.is conversation to their congregation in a transparent way.