Hopefully, you made it to my recent podcast. If not, here it is.

Do you think through the lens of your stakeholders often?

No matter what role you get hired for in data analytics, you have to focus on solving business problems, not scientific theories.

Most data science projects have no clear monetization goals. The value they provide is in limbo. The marketing hype continues, just with a different name — AI or Machine Learning.

It doesn’t matter if you solve their problem in Excel, or some “lame” tool in data analytics, as long as your solutions are of sound engineering principles and don’t introduce more manual work.

Be useful to your stakeholders. It doesn’t help them if you’re just being cool. People often complain about why the business doesn’t understand data analytics.

Do you explain yourself well?

Be honest, how many data people do you know are excellent communicators?

On top of that, you try to sell them some “data science” solutions to a problem they can’t define without professional help using your broken communication skills.

What good can come out of that?

Here are the 4 stages of stakeholder-driven data analytics journey:

1) Provide Information That Wasn’t Available Before

The business has legacy systems, and it’s almost impossible to integrate data from different source systems.

With modern cloud architecture, whether it be hybrid or 100%, the business for the first time can do cross-department reporting, enjoy automations, and eliminate hours of manual work.

This is an infrastructure upgrade, a necessary first step.

2) Guide Interpretation of Data Results With Stakeholders

Once you’ve transitioned the company to the 21st century, you get to spend more time interpreting the data with your stakeholders.

They start to think more strategically about what they want to do with their data.

You’re there to coach them and come up with fun use cases that you couldn’t explore before. This is the time you solidify your relationship with them. Be intentional.

3) Use Insights to Monetize

After a few successful use cases and getting beyond just reporting functions, it’s time to focus on monetization.

Now the business gets a taste of how successful data analytics looks like.

You can create products or tools that help increase sales or save costs.

You can predict seasonality of sales, margins of each factory production, etc.

There are endless ways to gain insights. You can even sell your data to other companies if you have enough data volume in your niche.

4) Collaborate to Scale Up

Continue to collaborate with different departments, help people reduce manual work, provide insights, and train staff to achieve self-service.

It’s only a matter of time for them to learn and join your effort.

Your company becomes truly data-driven in this stage.

If you can focus on what the current data pain points are, you’ll be successful at providing good solutions.

This is the way of Data Concierge Agile — always focus on your stakeholders.

Going through the last phase of book formatting for hardcover, regular copy, and ebook versions, estimated launch date: end of this June!

If you're interested in talking to me directly, I'm available on Clarity.fm:

If you like me to

1) guest post on your platform,

2) provide copy writing service, and

3) help with data project management.

Feel free to book a discovery call via Calendly here.

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I'm now available for podcast guest appearances! You can find all my details and get in touch to book interviews via this link below.

https://www.matchmaker.fm/podcast-guest/mo-villagran-f84572?utm_source=social&utm_medium=referral&utm_campaign=profile

If you'd like to give better presentations at work and hone your public speaking skills, let Christopher transform you into star speakers.

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