Managed Analytics — A Shortcut to Success
Summary: If you’re having trouble getting started with data science and predictive analytics, a managed analytics program may be just what the doctor ordered.
If you’re a fortune 1000 company, one of the ecommerce giants, or one of the Big Web User companies, read no further. You are the 20 in the 80/20 rule. You already have invested in predictive analytics and have fully embraced both the strategic and tactical value it offers.
However, if you’re part of the 80% in this rule, you are likely somewhere between putting your toe in the water, and outright non-adoption. The 80% isn’t just a made up number. Gartner reports that at most 20% of companies are engaged in real data science and predictive analytics. And that’s what’s reported by Gartner ‘responders’ who are more analytic-savvy and larger than most.
Yes there’s a practical lower end to this scale, companies too small to be able to absorb the investment of a small but full time advanced analytics group. In our earlier article ‘A Step-by-Step Guide for Getting Your Company Started with Predicti…’ we estimated that minimum size in the range of $50 Million to $150 Million annual revenue. But there is a huge gap in-between these smaller companies and the Fortune 1000 with thousands and thousands of companies who could benefit but can’t seem to get started.
For this group the idea of ‘Managed Analytics’ can have some appeal and we’re going to explore some of the pros and cons here.
Managed Analytics is outsourcing plain and simple. Find a talented predictive analytics organization that provides staff, tools, expertise, and experience and make a medium to long term services deal.
Companies offering Managed Analytics aren’t tough to find. Gartner and Forrester both have listings. In their case however, they list only the largest (and most expensive) providers such as Deloitte, IBM GBS, and Infosys.
But the fact is that there are tons of mid-size data science consultancies that will offer this service. This includes many who are also platform developers who also have strong service and implementation groups who would be happy to strike a deal to bring their expertise (and their platform) into a longer term relationship.
Any mid-size company can start a predictive analytics center on their own but they face two challenges, both real and perceived. 1.) The real and perceived problem of hiring the right talent in the face of today’s DS talent shortage, and 2.) Not knowing exactly how to get started.
A Managed Analytics arrangement of two or three years duration can be a quick fix for both these problems. These data science workers will be contractors in your organization and probably a third to a half more expensive than a direct hire. But they can hit the ground running and they ought to be able to deliver something valuable within the first 90 to 120 days.
If you’re managing this correctly and have made this agreement in advance, you can slowly phase out the contract data scientists with your own folks and have appropriately paced knowledge transfer. At the end of the agreement your people are fully trained and in charge.
Some Managed Analytics providers will structure the deal to allow you some flexibility in offering full time employment to their temporary staff. However you find them, there needs to be a parallel path of permanent hires that begins as soon as the ink is dry so that experience and skills can be transferred. A few mid-level folks may be analysts you already have on staff who are enthusiastic and capable of being trained up. However, the top half should be fairly senior and experienced data scientists and big data practitioners depending on your circumstance.
There’s a saying in consulting ‘no one ever got fired for hiring (name of big name firm here)’. And while that’s true, the Forrester and Gartner reviews point out that even the largest providers are subject to resource turnover.
Posted on 7wData.be.