An Easy Way to Spot a Low-performing Analytics Team

What having a go-to-market “Insights Manager” says about your analytics leadership

Topics:   Featured
Nov. 17, 2020
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After having discussions with dozens of sales leaders in the past few months, a couple sales leaders have sent me requests asking if I could recommend a good “Insights Manager” for their team. After some basic querying through job postings on LinkedIn, I realized go-to-market teams are hiring data experts more frequently. The role can be called “Go-to-Market Analytics Director” when a leader is needed, or a “Sales Analyst” as a more junior version of role. Whatever the job title, it is clear these sales and marketing teams do not have – but need – someone that can make sense of their data. This article is not intended to be critical of the talented person that often occupies this role, but rather their organization.

Often, the job description for this role can be summarized simply as "a data scientist with business acumen and communication skills". Five years ago, you might have described such a candidate as a unicorn. But today, consultancies, business schools and certificate programs are churning out people with these qualifications.

For go-to-market teams with this need, the role is vital. They need an analytically-minded person to manage the sales funnel, quantify the value proposition, or pitch to prospects and clients. Upon further research, I was also surprised to find that many companies hiring for role also have a centralized analytics team (e.g., an analytics executive with his/her own reporting pyramid). Given this, I had a couple realizations:

  1. The GTM teams (e.g., sales, marketing) are under-served by their analytics function
  2. The analytics leadership is missing an opportunity to play a more influential role

Rarely, the need for an Insights Manager by design. It is an exception to the rule, but executives at some companies actively eschew the analytics center-of-excellence model. These forward-thinking executives pursue an “embedded” model for analytics work, placing analytics specialists wherever they are needed – for example, inside marketing, sales, operations and finance independently.

But more often, this need arises by accident. Embedded analytics teams can spring up out of necessity rather than organizational strategy. These companies already have an analytics team, but for whatever reason, this team cannot respond to the needs of the go-to-market functions. Sometimes, the analytics team is too slow to respond to requests for help. Or, the analytics team is ineffective at communicating its findings to executives. And often, sales teams are not comfortable putting your analysts in front of prospects and clients. Regardless of the reason – this is a recipe for organizational conflict and redundant work.

Why does this happen? Why are analytics teams underserving business-critical and revenue generating functions? From what I’ve seen, there are a couple reasons:

  • The analytics team is too junior: This can happen at companies where the analytics function is not strategic. When leadership doesn’t value analytics, it cuts corners with the analytics budget. These executives get underserved by hiring junior analysts and data scientists lacking in business acumen and executive presence. If lucky, these organizations have a hired an analytics leader with vision that can advocate for their team going forward. But otherwise, these organizations often reap what they sow.

  • Your analytics leaders fail to understand your business: If your analytics leadership comes out of an engineering organization, you're at risk for this one. Engineers turned analytics leaders can silo themselves and not grasp the scope of how analytics can drive an organization. Or worse, an analytics team can take more pride in the complexity of its models than its impact on the organization’s bottom line. This analytics team is probably comprised of data scientists and engineers doing excellent work on the wrong problems.

If I were still running a centralized analytics team and found out one of my go-to-market teams was hiring an Insights Manager, I would have to question the value I am delivering to my company. And, hopefully, if it were not too late, I would be able to see it as an opportunity to step in and grow my team into a business-critical function.

To wrap up, I have to plug presalytics.io. Whether you are an analytics executive that wants to step up or a go-to-market leader considering hiring an Insights Manager, Presalytics is for you. Presalytics.io’s python libraries, middleware, and add-ins allow your analysts and data scientists to build content and visualizations that your executive and go-to-market will enjoy using without changes their workflow. Presalytics simplifies collaboration between engineers, data scientists, analysts and go-to-market teams, so everyone can use the tools they prefer to collaborate more cohesively and cross-functionally. Analytics leaders can use Presalytics to extend their influence without changing their analysts day-to-day or breaking the budget.

To learn more about presalytics.io or have a consultation, feel free to reach out to me at kevin@presalytics.io.

Kevin

Founder, Presalytics.io