A mix of internal analytics teams that know your business priorities and external partners that can add outside perspective, industry knowledge and first-hand experience is the recipe for success.
A key first hurdle for many organisations is deciding exactly what their analytics team should look like. The size and structure of your team will depend primarily on what you are trying to achieve, your chosen business model for delivering analytics value, and how you define ‘the team’.
Whether it’s to improve the quality and speed of your decision making, gain deeper customer insight or drive efficiencies into business operations, the common denominator for success is an effective analytics team. Many studies show the concrete benefits of becoming ‘analytics enabled’, but what is much less clear is how to build that capability within an organisation.
Larger organisations usually have two cyclical dynamics when approaching analytics - the external team/internal team back and forth or the centralised/specialised rotation. Building a sustainable analytics operation starts with identifying which cycle you're in and what's limiting your team's success.
This is when companies routinely swap between partnering with external experts and building internal teams, and expecting both to reach the same outcomes. This may happen every few years when leadership changes, budgets shrink or expand, or when a breakdown in the external partnership occurs.
When companies switch between wanting a centralised view on all analytics and wanting specialised teams working on specific outcomes. This often manifests by switching between a huge analytics, data and IT team that oversees all business units, and integrating specific experts within each business unit - think analysts that work in pricing, sales or marketing siloes. This cycle can also happen from leadership change but can bring its own set of risks.
When analytics expertise is distributed, people wish that more sharing, learning, and efficiency could take place – so they centralise it. Once that’s done, they start to feel that the team is disconnected from the business units – so they decentralise.
High-quality decentralisation is not scalable because it relies on too wide a skillset being held by the person or small team working tightly with the business unit, and leads to pockets of excellence which are not leveraged across the organisation.
In our experience, you can mitigate both of these cycles by locking yourself in the following dynamic.
1. A hybrid model where all business-as-usual and common specialist ad hoc work can be covered by the internal team, with an outsource partner providing less-used specialist expertise and overflow capacity.
If you can afford an analytics team of more than eight and some budget for a partner, the hybrid model and centre of excellence combination is the most likely to give you a successful outcome. When looking at your internal capability, understanding what kinds of skills you need is just as important as knowing how many people you’ll require. This will change over time as your business needs change and your general analytics capability rises — not just in the analytics team, but also in the business users who are exposed to addictive analytics.
Development of capability usually follows three phases; it is very difficult to leap ahead and almost impossible to leap ahead efficiently:
1. Heavy focus on data manipulation, automation of manual tasks and requirement gathering
2. Value added through insights and better information for decision makers
3. Value added through automated decisions and analytics that are directly operationalised into business processes
When it comes to focusing the team on areas that will produce value, it’s easier at the top end — so identify two or three really important analytics projects and let them get started. Build your capability to deliver on those use cases and then expand from there. This ensures you don’t build capability you don’t need. After the big wins, you will still achieve a lot of value from your analytics team, but it will require more effort directed towards defining exactly what that value is and prioritising projects.
This is where an outsource partner comes in handy. They will typically have been exposed to organisations in similar situations to your own, and will be experienced in identifying and defining the value opportunities in your business. If your governance process is good, then you will achieve a strong return on your investment without having to worry about fitting these projects into your analytics team workflow.
Keys to success here are central visibility and permission for business units to engage the partner if their work is not getting into the analytics team's priorities. There should always be a checkpoint near the end of the scoping process to determine if the internal team should do the work or not. If you want to learn more about outsourcing your analytics capacity, see how we work with our clients today.