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I was approached by a company which was expanding its fledgling SaaS business. They were hitting ceilings in ways that threatened to stall several years of growth. For example, the size of their dataset was outgrowing the technology originally used. Key business concerns were the efficiency of their small Software Engineering team, and the ability to derive business intelligence to customers from their own (exponentially growing) data.

In order to establish the ground truth to build recommendations, I conducted code reviews, process reviews and interviews with all stakeholders and team members. I used CookieOnline's proprietary matrix template to score 4 areas:

1. Technical Landscape - How good is the tech (the code, architecture etc) as it currently stands.
2. Team Strength - How strong is the team relevant to the skills required
3. Business to Engineering Interface - How well is Engineering working with business and vice versa
4. Engineering Delivery - How well is the engineering function serving the business

What I found was encouraging results in some areas the business had concerns in, but severe limitations in critical areas. In this instance, key weaknesses were discovered in the first 2, impacting the fourth. Business to Engineering Interface was in decent health.

To address the weaknesses, I prioritised two actions. I proposed raising the technical bar through the recruitment of an experienced technical lead to mentor, and improve standards and processes. Secondly, their data architecture was no longer suitable for the amount of data they were holding. Also, they had aspirations to leverage it for their customer insights, on which large scale commercial decisions could be made, to optimise global spend.

I also proposed moving to an API first philosophy which would a) serve their existing systems behind one data gateway b) allow third party integration at the same time. This would be implemented with a phased migration away from their exiting data platform, in a way that would have minimal impact on the business. 

In the implementation phase I provided technical leadership to the engineering team for several months, to raise technical standards. Drawing on my network I recruited a strong technical focussed lead to take over. The results were a number of completed technical initiatives that improved quality and throughput of the engineering team. The resulting data API meant customer data could be reported on and insights derived in much more ways simply not possible before. Even allowing anonymous benchmarking across the industry, It also opened up commercial possibilities through far more frictionless third party data integrations.

Overall, the outcome gives the business a step change in capability and commercial opportunities. Furthermore, in house software development efficiency has improved, and the business is now leveraging scaling infrastructure technology to cope with increasing data demands. After 6 months of implementation, I conducted another blind review using the original scoring matrix. Overall, scores generally improved, highlighting the efficacy of the remediation work.