Empower Your Company With The Right Data Team

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Do you have the right data team to support your data analytics needs?

It’s likely unnecessary to build a large team like the ones at Meta and Netflix for most companies.

With the current climate, building up a sizable data team is probably a thing of the past. With new tools and PaaS, more processes are automated.

It means less people are needed on a team. The focus shifts heavier towards understanding the business than technology.

You should focus on what business problems you’re trying to solve. The rest of the things will fall into the right places.

Business Problems

You don’t need to be a data genius to know what business problems you need to solve.

Start with these simple questions:

• What reporting process is very manual and error-prone?

• What area of the business are you most concerned about? (Sales, customer service, etc.)

• How much budget do you have?

• How fast do you want to position the business better?

If you want to hire a data strategist, you can. But why?

If you don’t have answers to the questions above, no one would know your business better than you do.

First Hire

Now you’ve figured out the situation at a high level. You need to bring in an experienced business analyst with strong communication skills and technical skills, leaning heavily on communication. This is a role I call “Data Concierge”.

A data concierge — someone who is intimately familiar with tech and business to serve as a point of contact between tech teams and stakeholders.

Wait, why not start with a Chief Data Officer? You need someone close to the groundwork first.

A Chief Data Officer might be great when you’re mature enough to scale. However, at the beginning of the data analytics journey, you need a scout who is capable of many things.

It’s smart to start small.

The reality is most companies don’t understand what they need at the beginning of its data analytics journey.

If you don’t work with data, it’s impossible to gauge how hard something you need might take to be delivered. By starting small, you can afford the time to study what use cases will give you the most value.

Also, you need to consider how the leaders react to this initiative. Some welcome automation. Some don’t.

Data analytics initiatives imply that manual work is not appreciated, and that’s why you’re looking for an expert in data analytics to change things up. You’re not satisfied with the current state of insights you get from them.

It’s best to bring this up as a solution to remove their pain points.

Ease the transition.

It’s not an initiative to eliminate headcount. Although it sometimes comes to it, it’s never the main goal.

Team Structure

It’s important not to burn out your data concierge. It’s a lot of work to scope out what a company needs, especially when you have various legacy systems for your data.

As soon as you have a clear definition of your first few use cases, it’s time to hire a backend developer to help your data concierge to process data.

For a mid-size to large company (besides those huge tech companies), add a few more BI analysts and data engineers so your data concierge can focus on engaging stakeholders from various teams and build trust. He/she can also lead this small data analytics team.

Deliver Your First Use Case

Now you officially have a data team with bare minimum data analytics functions.

The first use case should be like free marketing to mobilize the rest of the company. They should clearly see the value in this. It’ll get easier to collect more use cases from them.

This is also the stage to get strategic. Not all use cases have an impact on the top line. The leadership team should decide this together.

Again, the data team you have right at this stage is still young. It’ll get better as you go through more rounds of deliverables.

Scale Up

It’s been about a year, and a few successful products are delivered by the data team. Depending on the companies, you’ll probably fall into these two categories.

Data Analytics as Decision Support (Internal)

Promoting from within does wonders for morale if the talents are present and ready to work towards it. Your first hire, a data concierge, can easily manage bigger teams and take care of more data analytics needs across different teams. On top of that, he/she can provide strategic solutions to mature the teams and stakeholder needs.

Data Analytics as Product Monetization (External)

If your company has moved beyond using data analytics as decision support, you’ll need an experienced leader that can take data products to market with a great track record. This leader will need to lead a larger team that builds out user platforms for subscriptions, sell data to a third party, and have experience in leading software engineers.

Now the whole strategy of the company has changed as well. Maybe the CEO or the Chief Marketing Officer can work closely with your data concierge until you find a right fit for the Chief Data Officer (or whatever you want to call it.)

Common Pitfalls

It’s always hard to set up the first data analytics program, no matter what level you’re at and what size an organization is.

These pitfalls are closely related to how the companies fail to scale according to its needs. There might be constraints on resources, timing, etc. Do your best and just be aware of these.

Understaffed

At least 2 people please. It really takes one data concierge that can communicate and understand business use cases like a pro AND one very technical person to perform the ETL, data warehousing work while the other is busy engaging with the business. You don’t want them to burn out. You’re in for a long run.

Relying Too Heavily on One Person

Somehow, even with multiple team members, the business relies heavily on the one that can communicate the best. It’s hard to even out the work and train up others at the same time, which leads to the next pitfall.

Not Training Internal Staff

It’s wise to train up stakeholders who are technically savvy already. One of the financial analysts on the other team at my company is interested in learning Azure Synapse/ETL, etc. from me.

I always welcome such individuals. This is one of many ways to scale up, possibly the most efficient way. You don’t always have to hire more people. Sometimes, a great team of contractors can do wonders, too.

Are You Ready for Your Data Analytics Journey?

Now you know it’s not about one team fits all. Your data team will be perfected over time as you go through your stages of maturity in data analytics. It heavily depends on the context of your business.

Here is your map again:

1. Find business problems to solve

2. Get your first hire, a data concierge

3. Set up a team, starting lean

4. Deliver your first use case

5. Scale up according to the business needs

• Data analytics as decision support: Promote from within

• Data analytics as product monetization: Find a go-to-market expert for data products

Avoid common pitfalls:

1. Not adding more staff as you mature

2. Relying too much on one person, it’s a team’s sports

3. Not training internal staff to mature with data analytics functions

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