IBM AI / ML Project
Case Study

What did the client need?

 IBM Garage is a new team inside the larger IBM consulting organization. The ethos of this high growth team is to attempt to solve business challenges using new edge technologies such as artificial intelligence, RPA, and machine learning. AI, ML and automation technologies are extremely powerful but only if the business need is understood. There is no point automating something if the business does not see the value.  IBM Garage is a team that dedicates technical resource internally to a client, requesting the same resource to be matched from the client to try to solve challenges. IBM invented Watson – which really was one of the first baby steps toward harnessing AI for business.  

The client needed a new team of consultants that were not only technical experts within data science, analysis, ML and AI, but also had the fine balance of business acumen. It was vital that the technical profiles could meet with stakeholders and uncover challenges that could be solved – rather than starting from the conclusion that AI/ML is appropriate. IBM needed 5 profiles at enterprise architect and technical sales levels in Germany to meet the huge demand to use the Garage solution.

 

Strategy – What was the plan?

We set up our search team to uncover consultancies that were niche specialists within the discipline. Rather than going for the larger consultancies that may have a practice of consultancies, we mapped out smaller players where the consultants would be acting as end to end solution consultants. We needed to uncover people that can analyse the business, the available data points and interpret this data into viable challenges and opportunities, and then have the ability to use technologies to solve the problem, the niche consultancies were the best place for us to hunt. We used our results based formula of 50/10/3 – to map, select and headhunt 50 relevant profiles per hire, achieving 10 interested and viable candidates, which reveals a final shortlist of 3 people. We replicated this search each time, putting huge efforts into reaching each person on our longlist.

The intense headhunting uncovered a huge pool of passive candidates, but a very small amount of active candidates. We designed specific marketing material for the passive candidates to be well informed about the IBM consulting team, Garage specifically, but also we put huge emphasis on the career path of a typical architect, from enterprise level, to distinguished engineer, to chief. This was a huge differentiator against competition, as architects find it difficult to follow a career path.

Results / Summary

Osmii were the only recruitment consultancy to fill all 5 hires within the Garage team – and the 2022 headcount of 10 new hires have gone exclusively to Osmii. We love the Garage team!

For more information on AI / ML capabilities as well as the work we have delivered for IBM across Europe, please contact neil.mitchell@osmii.com

Example placements made :

Practice Lead Data Science

Director Data

AI Consultant

ML Consultant

RPA / BluePrism, UI, AA

Architects / Pre Sales / Technical Sales

Back