Debating the need for Business Partners in Analytics teams: (2) For
This post is a response to Martin Squires arguments against Business Partners in Analytics teams.
Thanks to Martin for that engaging post & putting his argument eloquently. Despite agreeing with Martin on the need for Softer Skills training, I disagree about these roles. In this
Following the same structure as Martin’s argument against, I will argue that Business Partners can benefit Analytics and Data Science teams. Feel free to join in the discussion once you have heard both viewpoints. It would be good to hear from leaders with both experiences.
Here I go to see if I can persuade you…
Definition: What do you mean by a Business Partner?
I agree with quite a lot of Martin’s definition of the Business Partner role, but would add two elements.
Firstly, this role has a relationship management element (in both directions). By that I mean they earn the trust of both analysts & internal stakeholders. It is their responsibility to ensure both have confidence in their ability to represent their needs. Analysts must feel like Business Partners are one of their team, working to ensure work is used. Internal customers must feel they are commercially savvy & committed to success of that team too.
3 reasons for having a Business Partner role
The first reason I would give for this role is the enabling of someone to focus on such proactive stakeholder management. Too often analysts or data scientists are expected to do everything. To keep technically up-to-date, focused on agile problem solving and to somehow also fit in managing relationships with stakeholders.
The creation of dedicated roles for this enable the team to have people who take the lead in this skill. Yes, business partners will also need communication (perhaps data visualisation) skills and a level of technical understanding. But they can also lead the role modelling of stakeholder management, freeing up other roles to excel elsewhere.
2) Fit with transition to specialisms
Once Analytics or Data Science teams reach a certain size, often around 10, they need to change. Smaller teams have been able to
By including Business Partners in that mix, it enables other roles to specialise as well. So, the creation of such roles will often go along with creating dedicated Data Engineers, Modellers/Statisticians and perhaps Data Artists.
3) Understandable model for wider business
Over recent years, many business functions have implemented such Business Partner functions. It is common in large companies, to find that HR, Finance & IT all have business partners. When they work well, commercial leaders across the business come to rely on these trusted advisors.
As Customer Insight/Analytics/Data Science seeks to mature into a recognised profession, it makes sense to adopt familiar models. Other parts of the business come to expect such a service and know what to expect from a business partner. I view the need for such a role as the data & analytics department growing up.
3 ways Business Partners help Analytics teams
A) Providing a career path for commercial analysts
In the past, analysts too often had to aspire to become a manager if they wanted to be promoted. Gladly, most businesses have recognised the need for more senior technical roles. Gradually a realisation is dawning that a range of career paths are needed within data science and analytics teams.
Some analysts will excel at the statistical modelling work, others at coding, others at data manipulation. All are being recognised as new specialisms. The role of a
B) Addressing the risk of commercially naïveté
It can feel like you want the floor to open up & swallow you when your work is called out as commercially naive or impractical. Too many good analysts lack the domain knowledge or commercial understanding to make the recommend the actions needed. This is not surprising as it takes time to develop such knowledge & to keep up to date with a changing business.
Business partner roles are seeking to feel like part of a commercial team within the business. They should absolutely “know their numbers” and be able to identify implications & barriers to initial recommendations. In this way, their understanding can protect analysts from being undermined, without stealing their glory.
C) Prioritising what is needed most
When seeking to get their information needs met, most business teams will exaggerate. Either claiming that work is more important than it really is or creating false urgency to get the answer quickly. Business Partners should “see behind the curtain” to challenge such manipulation.
On the other side of the equation, business partners can also help in debates within the data & analytics team. To avoid vanity projects or investments that will become white elephants, business partners should be part of the conversation on project prioritisation. With an equal seat alongside technical leads, they should help identify which technical capabilities would be most relevant and actually used by business stakeholders.
What would you do if you couldn’t have such Account Managers?
Apart from arguing for their benefit, I would go with part-time business partners. That is select the most business minded senior analysts or managers in the team. Ask them to take on the additional responsibility of being the lead contact for a business area.
Such an approach lacks the benefits of focus & dedicated time, but it can help. Used alongside the idea of dividing up the FTE across the team so each business area that needs to be supported can only have so much virtual resource. Such lead business contacts can then be in charge of prioritising work for their business area. It often helps to challenge stakeholders back with what they are willing to take off the list in order to add more work.
What are possible alternative solutions?
My initial reaction is the above model, but if I assume that is not allowed then another is decentralisation. That is splitting up an Analytics Centre of Excellence to locate analysts within business functions. This can enable them to consistently work on the same products/channel/function and so develop deeper domain knowledge. It also helps develop relationships and perhaps shared commercial targets.
To prevent this just being a recipe for ‘cottage industries‘ I would retain a small central design authority. These people would be the technical leads for their disciplines (say data engineering, data science & analytics). They would set standards, ensure common tools and used and provide L&D services to help analysts in business teams continue to develop.
Are you for Business Partners now?
Now having heard both sides of the argument, how do you come down? Do you agree with Martin’s case for banning such roles, or mine advocating for them?
It would be great to hear your views and practical experience. Feel free to share these posts widely and comment in the boxes below.