Last week our team had the opportunity to attend the Gartner’s Data And Analytics Summit in Orlando. This is probably the biggest gathering of data industry leaders in the world. It was a great learning experience and validation of our thesis that for the most organizations, biggest data challenges are not about technology. In fact, when surveying CDAOs, Gartner’s team identified that 5 out of 6 biggest challenges for D&A initiatives were all people related. Here are the key takeaways we got from this years event:

1. Focus on the WHY

Data teams can be extremely skilled in executing their data initiatives, but without a clear, tangible reason behind the task, all that hard work can have minimal impact. Before jumping into building the thing, make sure there’s is business value to what you are doing. Use company wide goals to identify if your initiatives bring value. Good examples are:

• Mission of the company
• Monetary benefit for the organization
• Clear relation to one of the company’s KPIs (Key Performance Indicators)
• Improving the Brand of the company, for example better user experience for the customers

2. Embrace Product Design Thinking

Through the event, the Gartner team brought quite many frameworks for how to identify great data initiatives. However the fundamental thinking behind them all seemed to follow the product design principles. Figure out the personas, what are their core problems and validate your solutions - all these steps are a must before jumping to implementation. You can check out our post on Why Data Teams Need Product Design, to learn why it’s so important, and there are great books on this subject like “Inspired” by Marty Cagan, a crash course into Tech Product Design, and "The Lean Product Playbook" by Dan Olsen.

3. Communicate Value to Avoid Being an Expense

Too often the data teams are looked upon as a Cost of Doing Business, rather than a team that helps the company grow. This can happen if the data teams isn’t delivering clear business value as mentioned previously, however delivering value is only a part of the story, data initiatives are often not so straightforward, and as a result can be hard to communicate. 

If your stakeholders don’t get get what you are doing, getting a buy-in and creating trust certainly becomes a challenge. To solve it, make sure that you can link your initiative with a problem that the stakeholder is having, and communicate it in a way they will understand.

Good Example: "Reducing the number of late payments by customers" instead of "building a prediction model for payment analysis". 

4. Data Products are Here to Stay

Every second vendor’s booth at the showfloor was all about data products, and it didn’t matter if it’s an analytical tool, a data catalog, or a cloud platform - data products were everywhere. It makes sense! companies are putting more and more pressure on data teams to deliver ROI and product thinking is all about that - validating value of your data initiatives. You can read on how to think of data as a product in our post.

5. Don’t get caught up in Shiny New Things

It can be extremely tempting to implement something everyone is talking about in the industry into your organization’s ways of working, but while it might seem exciting, it can likely be just a distraction unless you’ve managed to validate that there’s clear business value.
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At the Gartner Event, the Shiny new Things was clearly ChatGPT, some speakers presented it as a way to generate synthetic data for analytics, others as a way to create readable stories based on data, and nearly every presentation would mention ChatGPT at least once during the session. And while all these examples do seem cool, you should always evaluate whether that’s a good fit for your organizatiom. Start by evaluating what’s the data maturity of your company, what are they key problems and then see what are the best opportunities to solve them, ChatGPT could certainly be a solution, but you need to to know what problem you are solving first!

Final Words

Gartners Data & Analytics Summit in Orlando was probably the most packed event of the year, with Key Data Exectuvies from all industries attending. If you want to learn about industry trends, and directly meet CDAOs from leading companies, this is the place to be. 

For us at Ellie.ai the event was a great validation of our core mission, bridging the gap between business and data people across organizations, and gave deep insights into further enhancing our data product design frameworks.