3 Skillsets You Need For a Great Analytics Team

The digital era has brought about many causalities for manufacturing. Businesses across numerous industries have been forced to close up shop, while those that survived are left with never-before-seen challenges.

Forward-thinking companies are increasingly looking for fact-based data insights to drive their business decision making. With increasing mutability in today’s customers, systems and mediums, CFOs and CEOs want evidence-based justification for their choices, and they are turning to predictive analytics software to achieve this.

What’s more, executives know that leaving important business choices up to subjectivity and opinion opens companies up to huge organizational risk with potentially catastrophic financial implications.

CFO responsibilities have grown significantly over the years, beyond traditional finance oversight into more strategic business transformation. These executives rely on financial analytics technology to provide actionable reporting that can help illuminate business problems, challenges and opportunities.

Perhaps even more importantly though, they are looking for ways to connect finance with people and insights in other areas of the business to drive change. Research confirms this. Finance professionals overwhelming agree that building the proper team with the right skills is the number one way to enable data-driven decisions within an organization.

For this reason, it is best to connect people in different business areas from the get-go when looking to implement transformational analytical tools enterprise-wide. Building the proper team with the perfect mix of talent is challenging, but ultimately reaps benefits long-term by connecting disparate groups and breaking down organizational silos. Forming an analytics team that bridges complementary skillsets from across business areas helps in all phases of software integration, from initial buy-in, through to adoption and maintenance.

For the best results, ensure your team has a combination of the following skillsets:

Data utilization and technology

It should be no surprise that your data analytics team needs some knowledge of data analytics. This skillset is traditionally found within a company’s IT department and should be a necessary stakeholder in implementing analytical software and dashboard reporting.

Team members with this know-how should understand the principles of data design including best practices for data modelling and visualization. Effective analytics software provides the ability to convert large datasets into understandable visualizations like charts, graphs and diagrams, and this team member should be able to provide expertise on successful data display.

Having an understanding of current and upcoming trends in technology is helpful when selecting an analytics software vendor. Someone well-versed in data utilization and technology should be able to determine what criteria vendors should be measured against and know the right questions to ask on the technical side.

While leading analytics software does not require coding and programming from the end user, having a teammate with programming expertise is still useful. SQL and Python, popular programming languages, may be employed by disparate systems you are seeking to integrate in your analytics initiative.

IT generally has good insight into core systems used enterprise-wide, which is extremely advantageous when you are looking to harmonize your systems with analytics software. A team member with this knowledge is beneficial when exploring ways to connect source systems to new applications.

Knowledge of software security is also a must as you will want to ensure that any new analytics software provides the levels of protection you need for your important business and finance data.

How you choose to house and maintain your analytics system will also be a large consideration, so having a teammate with knowledge of cloud architecture and on-premise hardware is also beneficial.

Keep in mind that while someone with an IT background is invaluable on your team, they are not likely to be the end user of your financial analytics software. Whatever software you choose to implement should be intuitive enough for non-tech users to navigate.

Behavioral

This valuable skillset is often overlooked for software implementation projects. However, having people with broad behavioral skills should not be ignored. In fact, there is a benefit to choosing a teammate with great behavioral skills as your team lead.

Behavioral skills focus on strong communication and project management expertise. Someone with this skillset should be able to understand and explain the value of your analytics team and project to others. This is particularly useful when looking to gain buy-in from executives and upper management for your software, or when you are seeking to boost analytics usage company-wide.

People with this skillset should be able to use impactful storytelling to clearly communicate the value of your analytics project in producing actionable, data-driven insights to support strategic goals. For this reason, they should also have an unparalleled ability to think strategically and understand the goals, challenges and opportunities within the organization.

As you progress through your analytics project, it is worthwhile having a teammate with the ability to take and distill critical feedback to move your project forward.

Your behavioral expert should also have strong negotiation skills. Implementation projects are often restricted by business challenges, budget and time constraints, so it is helpful to have people who can navigate these challenges smoothly. Negotiating for extended deadlines, more money or resources may very well come in handy when looking to scale-up your data project going forward.

Being service-oriented is another valuable behavioral skill to add you your team. This means being able to understand software usage from the user perspective, as well as challenging how workflows will provide high levels of service and value.

Program and project management are also essential skills your behavioral resource(s) should have to improve your analytics initiative. Being able to work well with stakeholders within the core team as well as those externally while managing competing priorities is truly invaluable to moving your projects along smoothly and quickly.

Technical Financial Knowledge

Building a data-driven organization requires a company to do a deep dive of their financial data to understand how customers behave. You want to be able to convert sales, profits and journal entries into usable insights that serve a strategic purpose enterprise-wide. Perhaps you want to a CFO dashboard to better understand financial variances in order to improve your consolidation process. Maybe you are looking to produce more useful profitability analyses in order to accurately predict future revenue. Whatever your end goal, finding these insights requires a solid understanding of financial information.

Having a resource (or resources) on your team with rich knowledge of financial technical skills ensures you are integrating the right information into your analytics software. A person with this skillset should be able to easily read and understand financial statements and pinpoint the information and data within that are drivers for producing useful insights. Being well versed in the common ratios and metrics used within your industry will ensure you are capturing the right information for financial reporting process improvement.

They should also have a deep understanding of the business trends that affect organizations such as yours, so that they can watch the markets and alert your team to any information being missed. Working with a deep understanding of your own business is essential too, and this skillset is helpful in connecting an understanding of financial data to the organization’s priorities set out in the company’s strategic vision.

Your finance resource should be able to provide insights on how and why certain financial data should be present for reporting purposes and explain its utility to the team and the organization.

Closing thoughts

Creating a team with complementary skillsets to oversee your analytics project ensures you are getting a cross-section of stakeholders with valuable insights involved in your project. It’s important to avoid an imbalance of skills within your team. That said, don’t expect that your team will have every skill and piece of knowledge available that you may need.

One common mistake that organizations make when fleshing out a project team is that they assume in-house resources can do everything. Don’t be reluctant to bring in external experts when necessary. This does not mean you should be overly reliant on outside resources, but rather, this is a great way to fill specific gaps that may be present.

It’s often useful for companies to bring in consultants early on to provide guidance, but then lean on in-house resources to bring the job to the finish line. Leading finance analytic vendors, like insightsoftware, should also provide your team a depth and breadth of knowledge through robust customer support at all stages in your project.

Moving your organization to a data-driven model requires input from a broad section of business areas. Bringing analytics software on board is of course necessary, but it is just as important to have the right mix of people and skills to integrate fact-based solutions efficiently.