September 30, 2019

TIPS FOR MANAGING YOUR ANALYTICS DEPARTMENT

This article is part of a four-blog series that takes an in-depth look at data visualization. Follow the links below to see the other stories:

WHO SHOULD BE ON YOUR ANALYTICS TEAM?

THE SECRET TO DATA VISUALIZATION SUCCESS IS IN THE USE CASE

SIX PROBING QUESTIONS TO IMPROVE ANY DATA VISUALIZATION SYSTEM

Tips for managing your analytics dept

Advanced analytics and data-driven decision making is a significant initiative for senior executives at the country’s leading enterprises. Indeed, according to a recent Forbes article, advanced analytics adoption soared from 17 percent in 2015 to 59 percent in 2018.

That’s a problem for organizations with immature management practices that want to provide an ever-increasing number of data visualization dashboards and insights to business units. Data professionals, whose skills are in high demand, don’t need to stick around waiting for the company to implement management best practices. If they feel underutilized or overloaded, they can quickly move to a better job with clearly defined roles and responsibilities, reasonable workloads and well-managed projects.

At WebbMason Analytics, we help many of our clients streamline their analytics organizational structure. We develop the management frameworks they need for a smooth-running department and help them identify the roles and skills necessary for designing and retaining a high-performing team.

Focusing leadership on two significant challenges

Leadership has many facets, but there are two key issues we see come up again and again in analytics departments of all sizes. Both are related to creating a comfortable and productive working environment.

In the analytics organization, this often relates to maintaining an appropriately staffed team to manage processes. Understaffed departments, where people are overloaded or don’t have the right skills, are stressful places. If employees do not feel their skills are being properly utilized and developed, they are likely working with recruiters to find a position that is better suited to their specialized abilities.

Likewise, frustration rises when analytics team members are bombarded with project requests. Senior management needs to ensure best practices are followed in regards to project intake.

Managing expectations with the internal customer is another problematic area. Advanced analytics is new to many stakeholders, so leadership needs to be prepared to educate and remove obstacles. To do this, the lines of communication need to be kept wide open across all levels of the organization so everyone understands what’s being developed and how they can facilitate the overall goals.

Turning meetings into successful communications channels

Meetings bring people together to share information and encourage collaboration.

To be effective, they need to have a clear purpose and involve the right people. As a rule of thumb, decision-makers need to be invited to strategic meetings, project leaders and managers should be at status reviews and team members need to be involved in project sync-ups.

The daily stand-up, or scrum, is an excellent example of a purpose-driven meeting with specific attendees. It is designed to empower team members to organize the day’s priorities for a particular project.

Developing reporting structures that facilitate collaboration and growth

A clear reporting structure goes a long way to maintaining and protecting boundaries between roles so that everyone knows exactly what they should — and shouldn’t — be doing.

It all starts with comprehensive job descriptions that define each person’s role and responsibilities. When every team member knows where their job function begins and ends, they also know when to hand work over to another specialist. This is particularly important in a growing analytics department where people are transitioning from wearing multiple hats to increasing specializations.

For example, if an analytics department with a business analyst decides to add a data analyst, the original employee may need to relinquish many data processing tasks to the newly hired specialist.

Documenting asset ownership and governance

From tools to solutions to data sources, all analytics assets need to be supported and evolved until the day they are decommissioned. By documenting asset ownership, someone is responsible for the lifecycle of each asset. The enterprise avoids accumulating tools that aren’t being used, dashboards that people don’t trust and databases that have become dirty through lack of attention.

In addition to assigning ownership, a data-quality team should monitor databases and other assets. By running regular checks they can find problems with both data and systems.

A well-run analytics department helps an organization recruit and retain top talent as well as deliver valuable solutions and outcomes to the business units it serves.

LEARN HOW TO STREAMLINE YOUR ANALYTICS DEPARTMENT