In this episode, Jason talks to Paul Briley, an extremely experienced leader in data who’s worked in different industries, and now helps our customers to develop and grow as a key senior member of the team at Cynozure.
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If your data teams are set up well, it’s possible to launch data products quickly to a high standard.
[00:35] Paul’s experience in management and data, and how he became involved in commercial data leadership
[05:10] Why having commercial experience in data is valuable
[08:00] How different roles changed Paul’s perspective in taking data products to market
[14:30] Looking at every organisation as a ‘market’
[16:43] Input and direction from data experts vs. the company itself
[20:11] Communicate your data strategy and work to other departments
[24:32] Balance fast launches vs getting the product right
[32:00] De-mystifying some new roles in data
Every business has its own specific needs, which is why it is important for data solutions to be tailored accordingly. In order to maximise the benefits of data analytics, it’s necessary to understand what an organisation wants to achieve. Only then can the most appropriate data solution be put in place.
By working with experienced professionals, businesses can identify and implement the most effective data solution for their unique requirements. This can help them to gain a competitive edge in their industry and improve performance across all areas of their business. This customised approach to data and data products typically provides the most optimal outcome for the business.
One way to ensure your solutions are tailored for the business is to parallel your business campaigns with the development of your data product. This way you can make the two work in tandem, so your data product is ready for primetime when your campaign concludes.
Creating a data product is hard. So is making it fast and perfect. Launching a data product quickly and then iterating on it to make it perfect is often the ideal approach, but can be difficult to achieve in practice.
One way to keep momentum on innovation alongside the ability to create data products is a lab and factory approach. The ‘laboratory’ is where you can experiment with new ideas and methods. It’s a place for creativity and exploration. The ‘factory,’ on the other hand, is where we take those ideas and turn them into products or services that people can use. It’s where we perfect our processes and make sure everything works perfectly. Data needs both of these environments in order to be effective.
The data team is the brain of the organisation. They’re responsible for data analysis and providing insights to the leadership team. The leadership team, in turn, uses these insights to make strategic decisions for the organisation. When it comes to data strategy it can be difficult to find a balance between the two.
Leadership teams need to be able to trust their data teams when they provide them with insights. They need to have faith that the conclusions drawn by the data team are based on a sound methodology and analysis.
The data team needs to be able to communicate with their clients in a way that is both informative and persuasive. This requires the ability to understand the client’s needs, as well as ability to explain the data in a way that’s easy for them to understand.
This is not an easy task, but it can be done with a few steps:
1) Understand what the client’s goals are, and what they want out of the project
2) Gather all relevant data and present it in a way that makes sense for the project
3) Present findings in a clear, concise way so they can be easily understood by the client
You can also train people in other departments the basics of data and its potential value to their work. The data team should also have a strong understanding of the goals and objectives of other departments so that they know what questions to ask when they need information from them.
In the business world, time is money. The faster a company can gain information, the more likely it is to be successful. However, many data teams struggle with this process, and can find it difficult to create a data product quickly and efficiently. With the right approach, you can easily set up your data teams to be innovative and efficient, maintain clear communication with stakeholders, and align with the businesses goals.