Ethics and AI: 5 Issues Facing B2B Marketers

Data Fluency Part 2: How to Set Up Centers of Data Excellence

By Ray Estevez
Chief Information Officer, True Influence

(In Part 1 of this article, Ray looked at the skills needed for data fluency on B2B marketing and sales teams. Here in Part 2, he explains where to build centers of data excellence and expertise.) 

Understanding, managing and analyzing data is now everybody’s job in B2B sales and marketing, and the skills needed for these tasks are at a premium. Everybody – from the C-suite to entry-level marketing ops – should be fluent in data. This gives teams and leadership the tools and skills to quickly access data to make the best decisions in real time. 

Where to Organize Centers of Excellence for Data Fluency

Think about how you can make the best use of the data skills you have and the ones you plan to add. Where should you build centers of data expertise within your organization? The answer depends largely on the size and complexity of your operation. 

These four teams will be actively involved in using your data and you’ll want them to possess data fluency. They might be where you’ll want to concentrate strong centers of different data skills within your organization.

1 – Marketing and Sales Teams

The key driver here is the need to react quickly to campaign performance and market shifts. Having to request a new report or dashboard from IT is a delay that marketing and sales really should not have to cope with. Fortunately, most modern marketing and CRM platforms include intuitive query tools and what amounts to drag-and-drop dashboard construction.

Marketing and Sales should have internal staff (or at the very least, a dedicated support team) that’s expert in creating reports, segments and dashboards with existing tools. Really, it’s a plausible goal for all marketers to understand the reporting and ops GUI for your selected platforms – these tools have become highly intuitive.

If your company is large enough to dedicate a data support team to Marketing and Sales, then these teams should also have SQL and other advanced query language skills. Some data platforms, such as our partners at Snowflake, include the option for SQL-type data queries and other advanced matching and query logic tools.

If you’re not big enough right now to have a dedicated data support team, I’d suggest looking for data query and analytics skills, perhaps in an MBA-level job candidate, for your next hire. Again, the idea here is to be quick – you simply don’t have a week to wait for an answer while IT queues up your report request.

2 – IT Teams

In general, I’d say the trend is for IT to house less and less of an organization’s data skill sets. That trend is likely to continue, as reporting and analytics move into operational teams (as we just discussed), and advanced data applications move into specialized business units (more on that a bit later.)

IT will remain the hub for large scale data handling and storage, with an emphasis on encryption and security. These remain largely hard-wired technological issues. IT will also retain a final say on which third-party services and platforms can be added to the data environment. For the time being, advanced data science initiatives primarily live inside IT, but I certainly see that changing over the next couple years.

3 – Data Science and AI Teams 

Larger companies are spending on talent in AI and machine learning to find advanced patterns in their data, and these skills are finding their way into mid-size organizations, as well. Many companies are still using third parties for custom advanced data analysis, although a growing number of SaaS companies are offering tools that an MBA or other data-minded talent can master.

As these tools mature over the next two or three years, smaller companies will follow this trend, as they did with marketing automation and other martech stack components.

I can’t stress enough that these are not theoretical applications – this tech is here today. A piece at MarTechSeries advocates “a basic understanding of AI and machine learning” to help marketers understand how these tools will help them. Again, marketers don’t necessarily need to know how to implement these processes right now, but they do need to be fluent in core concepts. 

Think this isn’t a current reality? This interesting piece at MarketWeek notes that in a recent survey 30 to 40 percent of CMOs say they are cutting market research. They’ll be using tools like advanced lookalike modeling to backfill those areas. They also need better return on investment in analytics. Big Data skills and data fluency will be required to meet both goals, and increasingly companies are going to be bringing these advanced skills inhouse within their own specialized teams.

4 – Data Teams

Every day, I see more and more companies spin up free-standing data teams to oversee governance and access to data. To be clear, I am not talking about security or storage here – I mean the use of data. Who has access to it internally; what partnerships affect and define the flow of data; how it can be applied for business purposes.

These teams govern who can touch, handle and manage data, which is as much about ops and policy as firewalls.

This may seem contrary to my point about reacting quickly to the need for a new report or segment, and on some level that’s unavoidably true. The key is to determine which guidances are global to your organization, and which are specific to only some divisions, and organize for maximum response time. This breakdown at Medium discusses how even a startup had to experiment with various data team structures – centralized, embedded, within business domains – to find the best solution, and the process is ongoing.

For the most part, I think these teams are best left centralized in small and medium-sized organizations, breaking out into business domains only in larger companies.

Skills needed on the data team run the gamut, from expertise in legal regulations and company reputation protection, to understanding the technical tactics for getting data where it needs to go, as quickly as possible. A key function for the data team is reviewing and approving data flow between integrated systems.

Data Flows Through Your Entire Organization

Data fluency — understanding, managing and analyzing data — is now everybody’s job in B2B sales and marketing, and the skills needed for these tasks are at a premium. Everybody – from the C-suite to entry-level marketing ops – needs the tools and skills to quickly access data to make the right decision in real time.

You may want to look at some of our other articles on intent data for Sales and Marketing.

How B2B Intent Data Accelerates Revenue in 2021

B2B Leaders Go All In for Sales, Marketing and Data Alignment

Expand the Impact of B2B Intent Data: Where to Start?

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