Putting aside my soon to be wife and Seymour the office dog, there is nothing I enjoy more than building something and seeing it work in the flesh. In my field of work this would be building a piece of code and seeing it do what was intended for it to do. A recent example at CluedIn was seeing our Clue Processing Pipeline taking Clues from the data that exists in all the tools we use and turning them into knowledge, where-after it would stream them to the team. Although conceptually simple, there is some pretty amazing engineering happening within this process to not only find knowledge in the data but also for the security, scalability and flexibility we have to introduce new processors into the pipeline at any time. This pipeline only came to fruition because of collaboration between the team. Discussions were conversed on Slack, notes were put in OneNote, meetings were had on Google Hangouts and our code was stored in Github. The real insights from how to build the processing pipeline, in fact, only came from some small notes that one of the engineers (Martin) had in his own Evernote notebook, combined with the idea of another engineer who read them. This would have never happened if this data was not shared. Martin thought that it wasn’t the best idea, but it sparked another engineer to think outside the box, given that information.
Which brings us to open, knowledge driven workplaces. Call it flat-structure, holocracy – there are varying levels of embracing the idea, that within an organization there are huge disadvantages in abstracting people away in typical hierarchical models or structures. The CluedIn team has already seen huge benefits from embracing an open work environment from day one. CluedIn monitors the data from the teams Calendars, Mail, Files, Chats, Discussions, Meetings and much more. Why? Because of moments like the ones we had above. To show that we are very serious about this, as soon as our spring release drops we will be publicly opening our own CluedIn instance to the public. That’s right! You will be able to see our roadmaps, internal discussions and even our dentist appointments. This might sound a lavish idea, but the intentions are sound, we are on a journey to prove that sharing knowledge (even if just internally) drives huge business value.
Take one minute to think about what is problematic with the organization you work in today. If you answered with any of the following topics then you could benefit hugely from CluedIn and the experiment we are running internally:
- Departmental Information Silos
- Office Politics
- Lack of Decision Making and Visibility of Decision Making
- Lack of Communication
- Trust Issues
- Blurry Visions
- Lack of clarity about who is in charge and who should makes decisions
- Decision Bottlenecks
- Lack of engagement
That was a sneaky experiment. Why? Because we already know that you will at least pick 3 or 5 (if not more) of these. Every office suffers from these issues, whether you are Google, CluedIn or Tesla.
So starts “The CluedIn Experiment”. Our hypothesis is that by enabling a “share all by default” ideology internally, coupledwith CluedIn to manage, distribute, enrich and surface relevant data to the team will enable us to not only work more efficiently, make the best decisions available but equally important – enable a work environment where trust is key, where the discussion that need to be had are done out in the open, not behind closed doors. How many times have you later been informed that “someone discussed that and we decided W, X, Y” where the right person for that decision could have told them about option “Z” but just wasn’t involved.
The catalyst is the easy part. The entire team is tackling this problem because we have experienced it our entire career and there has never been “the” tool that solves this particular problem.
The control will be one of the engineers on the team. Poor Martin 🙂 He has only been with the company two days and already he is the guinea pig in an experiment. We will simply be monitoring how “Clued In” Martin is to the office environment. This includes everything from “Who is in the office and when?” to “What decisions were made on the product?” to simply – “How involved he feels in the company?”
To add some dynamism, Martin and I sit in the same office, we have lunch together and are on the same “tea cycle”. For me, the interesting results will be how much does Martin learn from osmosis and how much he doesn’t learn from being disconnected from the data that the team is generating. This will include everything from code that the team is writing, decisions made on the business plan, roadmap schedules, marketing strategies and more.
You can follow the experiment on twitter @CluedInHQ where we will give daily updates on the results.