📝 MY NOTES #008 - Practical approaches to use case prioritization for optimal business impact

Theme - Working with business teams

Feb 06, 2024

Hello everyone,

Few weeks ago I had the chance to attend the Data Summit 2024 where speakers from different organizations spoke about a myriad of topics related to data. There were 10 sessions given by people who were CEOs, Data Managers, Data Engineers. Below are the titles of all the sessions I attended. In the coming weeks I will be posting my notes from each of these sessions & these titles will turn into links that you can use to jump between different session notes -

Why failed MVPs are your second most important KPI
📝 MY NOTES #007 - Why failed MVPs are your second most important KPI
Raghunandan Kashyap
·
February 1, 2024
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Let’s start with the 2nd session I attended-

Driving data-driven success: Practical approaches to use case prioritization for optimal business impact

Hosts :

Ash Dhupar, Chief Data Officer at BAE Systems

Ali Tore, Senior Vice President of Advanced Analytics at Salesforce

Fabio Italiano, SVP, Head of Data Tooling & BI at M&T Bank

Ali, Fabio, Ash, and Jose join for a discussion on the essentials of justifying and designing use cases in data function leadership. They explore the criteria for use case justification, apply design thinking to selection and discuss tailoring requests for organizational needs.

The conversation extends to fostering cross-collaboration between teams and emphasizes the crucial role of leadership in navigating the data landscape. Gain practical insights into creating a strategic, user-centric, and collaborative approach to drive success in your data initiatives.

Ali starts off the conversation by speaking about the stark amount of Analytics projects that fail, almost around 80-90% don’t enter into production mode. He mentions a few common causes he sees for these failures.

First being, the teams getting lost in Data scoping (Where do we get the data from? What kind of data we need? How do we set up governance and security?)
Another reason is that teams get lost in talent, they think they need Data Scientists or Subject Matter Experts while ignoring that they might need a complete cross -functional team to bring the project together.
Others of them get stuck with technology, they are so lost with the platform or the vendor that they forget to understand the complexities of the project.
Some fail on the cost side where they focus so much on budge constraints that they end up missing the value form these initiatives.

This is where Ali bring in the other hosts into the conversation by asking them about what things they look for in a project when teams come to them asking for budgets or trying to justify a use case ?

Fabio starts by answering, the real question is always How do we generate value together? How do we collect the right data points in the value framework? He sees essentially 2 driving forces -

The initial investment, strategic planning where you justify the big investment upfront with a mostly well defined business case.
2nd point, In analytics, Communication is key. It’s very important to constantly communicate value created to key stakeholders.

Ash joins the conversation, By saying it’s in reality very simple by just asking if that use case is solving a business problem or not?

Ali moves on to the next topic - Philosophies that businesses have - Let’s hit the low hanging fruit first, Let’s do a small incremental pilot project & on the other side there are businesses which talk about starting with the most transformative use case. Ali asks the co-hosts about how would they guide teams with these different philosophies?

Ash goes on to say that it depends on the maturity of the company and the team. He gives an example -

If you have a new team and you are planning a use case that will give huge value in a year’s time, he wouldn’t give a nod to that project because first there is a level of “you don’t know” what you will achieve. So if you are starting out your journey, you should look for small wins which will demonstrate your ability to deliver to your stakeholders and most importantly your stakeholder now know that they have value that they can work with for future projects.

If you are on a different level of maturity, when you have a team that knows what it’s doing, then taking risk on long term projects is definitely worth it.

Fabio agrees with Ash and says for longer projects data teams can buy from software developments projects the method of working in Agile methodology and giving value in small increments.

Ali goes on to the next topic by talking about the tension in projects when you are working with different kind of skills within teams, where business teams want to pick up cases that they have knowledge about where data teams might want to work on optimizing algorithms that might add more value according to them.

Fabio says the sweet spot is when you have upskilled the business users enough where they can have elevated conversations with data teams. He expects it to be accelerated with introduction of genAI. It also adds that Executive sponsorship is critical to advance the skills of the knowledge workers.

Ash gives his view in 2 parts -

About the tension, he never changes one golden rule which is - FOLLOW THE BUSINESS!! If you are going after a cool solution but no one is using it it’s a waste of effort, time & money.
At times business teams can’t connect the dots about what problems can be solved with use of AI, the techniques that data teams know about. Thus the lack ability to explain what is possible with analytics leads to this tension. Ash shares a technique he uses often with teams where he challenges them for a 90 day problem & expects value from projects within 90 days, if you are able to then you gain the credibility of being value generation team within an organization.

Ali asks the next question, How do you make sure that people understand the true value they are creating because they understand the pain points?

Fabio says it’s important for data teams to wear multiple hats, for example -

Use case engineering teams should be created who might be trained for design thinking skills, creative product design, rapid prototyping that will help the conversation tremendously.

The hosts end up by saying that we should not expect value creation to be a linear process, As you build knowledge, tools, upskilling then you will see spikes of productivity and creativity and hence you will see strokes of genius from the same teams!

The End…

What an insightful discussion it was in our recent webinar, The conversation shed light on the challenges and strategies surrounding use case prioritization and justification in data function leadership. They emphasized the need for aligning use cases with business problems, fostering cross-collaboration between teams, and maintaining a user-centric approach throughout the process.

How do you approach use case prioritization within your organization? What strategies have you found effective in driving data-driven success? I look forward to hearing your perspectives!

The Weekend Freelancer

📝 MY NOTES #007 - Why failed MVPs are your second most important KPI

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