In the last couple of months at The Data School Down Under, we have completed a diverse range of client projects. We’ve been lucky enough to work with clients from a variety of industries, including finance, retail, construction, and even a national sports team. Each project has presented a different set of data challenges to the team.
In this blog, I will discuss some of the techniques and approaches to these projects that worked best for us, as well as highlight a few common traps to watch out for.
With only 3 full working days to work with the client’s data, time is precious! As project lead, a great way to save time during the week is to pre-create the project folder structure for your team. This will save time both up-front and later in the project as everybody knows where to save their work. Having ‘sandbox’ folders and ‘final’ folders helps to reduce clutter and ensures everybody knows where to access their dashboards.
2. Client Communication
Successful projects will often start with clearly understanding the client’s expectations and priorities beforehand. Any briefing documentation will be essential in defining the client’s requirements. In addition, ensure that methods of data transfer are agreed, as well as preferred methods of communication to ensure any data queries are quickly addressed. If any ‘data dictionaries’ are available, request these also. Also, check which versions of Tableau and Alteryx your client uses – often enterprise businesses run a few versions behind.
3. Resource Allocation
Building on the client requirements, be sure to allocate the team in accordance with the workload and priority. Certain tasks may be more complex than others, so ensure that you assign your team tasks accordingly. Assigning an extra person to a high priority task can make a huge difference to the final deliverable dashboards.
4. Stand Ups are Great, but tailor them to the Project!
Stand ups are a great way to clearly communicate tasks and progress amongst the team. If you’re on a project with particularly complicated or messy data, then regular stand-ups can help ensure the team are on the same page and enables you to move team members between tasks. If you’re working with well-curated data, then fewer stand-ups may be required as everyone is clear on their tasks. Utilise Kan-Ban boards to keep your team task orientated. Remember to keep stand ups focused, sharp and update oriented – save the problem solving for after!
5. Time Box Tasks
When starting ambitious tasks, be sure to allow enough time to complete your other priorities. If you find yourself taking too long to complete a task, it’s probably better to park it and move on. If you have time later, then you can return to it. The aim here is to avoid task fixation and make sure you’re in a good position for the final presentation!
6. Thursday Afternoon Presentation Practice
Our team has hugely benefitted from presentation practice on a Thursday afternoon. It’s a great time for feedback on your dashboard from the team and allows the presenter enough time to implement improvements before the client presentation on Friday. Don’t worry if your dashboard is not polished and finalized – it’s about getting feedback and ensuring everybody is on the right track!
7. Settle on a Dashboard Template
Agree on standardized dashboard dimensions, colour schemes, logos and layouts in good time. In addition, ensure that filters, parameters, and highlighters are all positioned consistently within your dashboards – praise 2019.2 hide/show containers feature! Consistent dashboard designs look professional and lend weight to your insights.
8. Use other Data Schoolers!
Previous cohorts have all been through the client project process, so be sure to ask them for any project management tips. This is especially true for data schoolers that have worked directly with the client before – utilising their experience can give you a great head start on your project and will give you the best chance to impress on Friday!
Finally, remember to enjoy these projects. They’re a great opportunity to get to know a variety of businesses and make a meaningful improvement for their data analysts and overall strategy!