It is no secret that Big Data is Big Business. Fundamentally, Big Data is a natural continuation of automation, where companies can become much more effective with the same workforce, able to generate more business more efficiently, and pivot quickly into new markets.
Artificial intelligence and machine learning are general purpose technologies already starting to transform the global economy. They can be seen as new industries in their own right, but they are also transforming business models across many sectors as they deploy vast datasets to identify better ways of doing complex tasks – from helping doctors diagnose medical conditions more effectively to allowing people to communicate across the globe using instantaneous speech recognition and translation software. While the majority of large companies now have an AI strategy and analytics team, the field is advancing so fast that a group of people with a wider view across several industries are in most cases very necessary to instruct, train and bolster these teams in new developments. In other words existing analytics capabilities often “can’t see the wood for the trees”.
We aim to help companies become self sufficient in these areas with our depth of IT and automation experience together with cutting edge analytics.
Problem: “85% of Big Data projects do not make it to production stage” – Gartner (2016)
Why are we in the other 15%?
Its kinda presumptuous statement for a startup right? But… if you look at it from the perspective of our collective experience it makes sense. We are building projects into production today, and have been as individuals for more than a decade. We build for production. Under our current project methodology 100% of big data projects delivered by our team members have reached production successfully. Our strength lies in our blend of a tried and tested Analytics Ops methodology, extensive Management Consultancy experience, and very deep technical delivery experience in a wide range of Open Source technologies.
Analytics Ops / Data Capability Methodology
Analytics Ops is how we embed the flexible, experimental and fast moving world of analytics and data science within the more rigid, governed and secure world of enterprise operations. Connecting Technology, Organisation, and Governance, has evolved from DevOps, over years of work with the biggest enterprises and data consultancies.
- We focus from the outset on delivering value, and do so iteratively during any engagement.
- We work in partnership with our clients, through a product owner who is responsible, on the client side, for successful landing of the project and realisation of business value
- We aim for short-term, high-value partnerships on select projects to deliver maximum value. We do not engage in “body-shopping,” or long-term, low-value resource augmentation.
- We have experience in building the local clients team simultaneously while delivering the project with the aim to make ourselves obsolete as fast as possible.
- All projects are targeted at the relevant Production systems from the outset. Where the work is a proof of value, we develop this on systems that look like Production
- Where there is no Production, we will design and build it
- We develop solutions together with our clients, embedding both the solution and an overall way of working on analytical problems, building the workforce of tomorrow
Written by David, Rob and Mireille. David Floyd is a partner at Leap Beyond in the UK, Rob Lambert & Mireille Buiel are founders.