Hi everyone!

With a lot of help from people in my writing group, coach, and friends, here is the finalized book title:

Data Insights Delivered: 7 Proven Steps To Understand Stakeholders, Manage Expectations, and Deliver Actual Value

I sent off the manuscript to my editor already. It's just exciting that I actually wrote a book!

As for work, it's been pretty rough because we hit a Power BI-Power App limitation. We might need a CRM SaaS solution than our home-grew one. It's always hard to explain to the stakeholders that there is a limitation as to how far a technical product can go. Just gotta apply Data Concierge Agile to solve this problem.

This week we'll learn how to stop failing data projects.

How to Stop Failing Data Projects

How many times have your data analytics projects started with a bang and ended with a whimper?

It’s a recurring theme in data analytics.

When a company starts a data project, it usually falls on the data teams. The business just unloads their use cases on you, hoping it’ll work out. Although they invest a lot of money, they don’t know how to define use cases.

Communication withers.

Fatigue sets in.

Projects fail.

And this failure isn’t one-sided. The data teams don’t communicate well what they need from them either.

What They Think

The business:

“What I want is simple. We need a dashboard that shows our revenue by product. Why can’t they deliver such a simple thing?”

The data teams:

“The business has no idea how messy the data is. There is no checkpoint for data quality or anything. It’s hard to get hold of people to answer our questions. There is no rhythm, no aim, just work, and it doesn’t work.”

What Does it Take to Succeed?

1. Equal Ownership

2. Data Concierge Agile Project Management

Let’s dive in.

Equal Ownership

We can’t leave the success of a data project to chance. It’s expensive and can have a tremendous impact on the business.

What does equal ownership look like?

Both the business and data teams need to feel equally invested in a project.

What kind of relationship works when it’s only one-sided? That rule applies here too.

Both parties should meet as often as necessary to get the tech requirements done. There should be a few rounds of back and forth. This is normal as data projects are complex, and the requirements change often.

One meeting won’t do it. Spend the time to get a plan together.

Be committed to make this happen.

It’ll also help if data teams are embedded within a department who is the biggest consumer of data analytics or share budgets with another team.

Data Concierge Agile Project Management

Once you have the commitment from both the business and the data teams, the rest is up to the data teams to perform and deliver.

Think about what concierge means.

It’s a role that assists guests with personal needs at a hotel and many high-end places.

Data analytics projects are highly customized according to the business needs. You must have a customer-centered mindset and be a concierge for your stakeholders.

You’re their data servant. As data professionals, you can’t expect the business to give you the exact tech requirements. It’s up to you to figure them out.

Many can make a dashboard and write some SQL code to build a backend database on the cloud. However, excellent service is your goal. The way you interact with your stakeholders speaks volumes.

Do you listen?

Do you try to understand them?

Data Concierge Agile aims to deliver a world-class stakeholder experience. There are 4 parts to this.

1) Data Accuracy:

Data presented has to be tripled checked. Don’t present erroneous data. How can you do that without domain knowledge? Stakeholders can help you.

They’re experts in their field. They can tell if the numbers look normal. Remember, it’s a partnership. You don’t have to do this on your own. Invite them to solve problems with you.

Don’t be shy. They’ll appreciate that. It makes sure the final products are of the highest quality.

2) Regular Communication:

Be present.

The data teams disappear whenever a project starts. Don’t be one of those people. Set the tone for regular communication. Reach out and ask questions.

If you have no questions, demo progress and ask for feedback. Stakeholders love seeing progress and feeling included.

3) Equal Partnership:

Understand that this is a collaboration. They can’t do this without you, and vice versa.

It sounds simple. However, many just don’t get it.

I’ve been in many conversations where data teams fume over something that could be resolved by talking to the stakeholders first. They don’t understand why they have to do so much while the data is not usable.

Have you thought of raising that concern to your stakeholders and ask for help?

They don’t just give you questionable data on purpose. Remember, they don’t understand data like you. They need you to help them understand so they can come up with a plan to improve.

Practice equal partnership. If a data project fails, it’s everyone’s fault.

4) Trusted Adviser:

The business wants you to provide professional opinions. They may want a dashboard for their use case, but don’t realize what they need is actually an automated report via email daily.

It’s your job to make them understand the pros and cons of different options. They can make an educated decision with your help.

Position yourself as their trusted advisor so you feel respected, and they feel heard.

Are you ready to finish your projects with a bang?

Practice Data Concierge Agile now and never fail a project again.

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

Besides writing about data project management, I also write novels. I recently discovered this Podcast by Jim Woods. I asked him how to find an editor. He recorded a short episode to answer my question. I'm just impressed by people's kindness online!

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