Selecting Professional Service Provider For Your Business Intelligence/Information Management/Analytics/Big Data Projects
You've done all the right things by following your enterprise vendor selection methodology. You created an RFI and sent it out to all of the vendors on your "approved" list. You then filtered out the responses based on your requirements, and sent out a detailed RFP. You created a detailed scoring methodology, reviewed the proposals, listened to the in-person presentations, and filtered out everyone but the top respondents. But you still ended up with more than one. What do you do?
If you shortlisted two or more market leaders (see Forrester's latest evaluation) I would not agonize over who has better methodologies, reference architectures, training, project execution and risk management, etc. They all have top of the line capabilities in all of the above. Rather, I'd concentrate on the following specifics
People
- The vendor who proposed more specific named individuals to the project, and you reviewed and liked their resumes, gets an edge over a vendor who only proposed general roles to be staffed at the time of the project kick off.
- Who was present at the in-person proposal sessions? Only the vendor directors/partners (lower score) or the actual people who'd be running the project (higher score)? The actual project manager proposed to lead the project should've led the in-person presentation, not the practice leaders who you may never see on your project.
- Are the people who are being proposed to work on the project the same ones who were showcased in the case studies that were part of the proposal (higher scores) or were the case studies projects implemented by different individuals (lower scores)?
Process
- Agile analytics/BI practices are key to project success. Did the vendor proposal include agile project approach (higher score)? Did the vendor proposal include a project schedule with tangible deliverables no more than ~two weeks apart (even higher score)? Did the proposal featured case studies of projects that had agile "quick hits" tangible deliverables? FYI tangible deliverable is not a project plan or documentation. A tangible deliverable is an actual new app, or a new feature of an app that the end users can start using.
- While some of the commodity BI tasks can be offshored (testing, documentation, tuning, optimization, etc) Agile BI development methodology calls for face to face business/IT interaction. Whichever vendor is placing more people on site should get a higher score. Caveat: not applicable to infrastructure projects like system migration, upgrades, etc.
- Knowledge transfer. All consultants want to get their foot in the door and never leave. Did the proposal include a clear knowledge transfer, disengagement plan that clearly showed that the consultant meant to do their job and leave (higher score)?
Contract
- Confidence factor. How did the vendor estimate the effort? Did they just rely on your RFI/RFP (lower score) or did they send a few people to your location to find out more, dig through documentation, interview key stakeholders, etc( higher score)? Did they use a detailed estimation methodology that they shared with you (higher score)?
- Last but not least I'd give a significant edge to a vendor who's willing to share success and risks with you. I'd favor a proposal which has penalties for being late and bonuses for early successful delivery.