Project Learning Blog: Sometimes you should rely on your team.

This being the second time I’m doing the course, this assignment proved familiar in form yet it turned out to be somewhat unfamiliar in execution. I joined my team somewhat late due to registration issues, meaning that I missed out on the ideation phase. The group had already decided on what the proposal was going to be: a project based on one of our member’s jobs where there was potential for increased efficiency using AI.

Entering at this point gave me two different challenges as compared to other (similar) group assignments I’ve done so far. First it asked me to “jump in” without having the full context, which meant taking a different approach from usual group work. Instead of just being a part of the group and going with the flow I instead needed to be more proactive: to get up to speed and find a way to contribute as soon as possible. Then the second challenge was to work on something that I did not have any input on originally: the task at hand was one set out for me in pre-defined conditions and rather than staying purely theoretical had a real use-case behind it.

These challenges were not extraordinary, but run contrary to how I have often approached group work so far: I generally am someone who likes to challenge decisions and discuss all potential pitfalls before moving forward with something at least slightly safe. I like to have the full context but instead here I was left wondering at the details for a while: it took a minute to get in contact and get the information required, and once I was properly connected a lot of work was already done for the original proposal, meaning I had little possibility to correct course had it been necessary. Luckily, it was not.

At this stage then my main contribution was providing feedback and challenging some assumptions. The dynamic was a bit strange with one person having full context (it being related to their job) while the rest had only an idea of what the context entailed. This felt rather accurate or realistic to actually joining a company halfway through on their projects. There were a fair amount of questions to be asked and each answer revealed part of the information necessary to move on. Our proposal got through in one go: it was a clear and easy target in reducing workloads by automating certain steps in proposal creation and value demonstration using AI.

Originally this multi-step AI-assistance tool would mainly work in ways which many companies are already attempting to use: using transcripts from a call and using notes to create context for a semi-standardised form that now could be partially ready-assembled. A big step up came with the idea to also include a custom example of what the product (in this case BI dashboards) would look like in the customer’s context. Now we were slowly starting to move from just a workload reducer to also a more effectively converting process, as medium-low conversion rates leaves the company a lot of room to improve. The next iteration would be to form a new introductory offering model surrounding this AI-enabled example. This would be a partial try-before-you-buy for bigger projects, while also leaving smaller tasks potentially auto-completed.

Because a lot of this process was basically applying existing ideas together to create a solution for the specific company we had in mind, there were few surprises along the way. Mostly we had to focus on making sure the project was as air-tight as possible. This was surprisingly difficult for me as once we started moving forwards with the presentation after the demo was done, we had to put a lot of the context that was now becoming more natural into hard evidence and numbers. Working with numbers that are a given rather than estimated or something I could validate myself meant there was a lot of communicating back-and-forth on the context whenever something had to be re-defined or changed. During the finalisation of the presentation both as a group and individually a lot of effort was put into creating alignment between the slides.

The key take-aways for me were mainly related to the nature of my involvement rather than the course-specific context. It being the case that I’m now doing this course for a 2nd time and have completed the other courses already, the business strategy context and how we ended up utilising AI in our example did not really come as a surprise. There is some added value in the changes between last year and this year’s coursework, but a lot has stayed the same. We might currently be in a phase of consolidation where we are looking to actually integrate these new AI capabilities rather than chasing any new possibilities. I think that regardless of the future models this proves even more so that the fundamentals of a business and having things in the right place will prove to be important to stay adaptable as tools simplifying capabilities slowly roll in.

Upon reflecting now on this assignment and some of the job interviews I’ve had so far I see many similarities between the approach I had to take here and the approach that is being asked from me in the positions I’m applying for. There’s great value in being proactive both in the areas you already understand and in admitting you don’t know what is happening when you lack the context. While being behind could mean falling further behind in a solo project, as a team collaboration sometimes also means putting effort in making sure everyone is on the same page.

My role wasn’t as extensive as I had liked it to be, nor did I feel I could utilise my skills ideally, but that’s also part of reality. I instead got to further solidify information for the others at first, and got to and wanted to fill in the gaps when and where I could to make sure I contributed my fair share. Still I’m somewhat dissatisfied: I didn’t do as much as I could, but I think I’m worthy of having my name on the project nonetheless and that I truly did add things that otherwise wouldn’t have been there. As the old adage goes: the perfect is the enemy of the good. The teammate with the personal connection was our spearhead, and we were able to push together with him towards a final product that stands up to the tests given. My challenge wasn’t to create the best project, it was to contribute as much value as I could from a somewhat limited position, and I think that I did succeed in that. If I were to be put in a similar situation in the future, I might be able to find a bit more peace and strength from such a position, which is a fine learning achievement in my book.