Jason, host of the Hub and Spoken Podcast, recently released a brand new book “Data Means Business.” In the book, Jason deep-dives behind the scenes of successful businesses that harness the power of data and deconstructs their processes.
In fact, this episode’s guest Robert Barham and Gousto both, are featured in the book.
In the latest episode, Jason talks to Robert Barham, Director of Data at Gousto which is a meal kit company. Gousto has achieved tremendous success and became one of the first food companies to be valued at over 1 billion pounds at the end of 2020.
Listen to this episode on Spotify, iTunes, and Stitcher. You can also catch up on the previous episodes of the Hub & Spoken podcast when you subscribe.
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[02:00] Rob’s journey in data before he landed his current role at Gousto
[03:50] What ‘data native’ means and why it is important to integrate a data native approach early on in your business.
[08:00] Rob’s role and responsibilities at Gousto, and how the data team works alongside other departments to optimise the overall performance of the organisation
[19:43] What are data products and why you need delegated product managers even if they are not necessarily data scientists.
[24:35] How to hire team members into a digital native culture even if they don’t have data science qualifications
Like digital natives who have grown up with technology around them, data natives are those who have embraced data early on in their business.
Making your business data native is a cultural change. It allows your business and employees to recognise data’s integral role in improving a business.
Many organisations today are experiencing a cultural shift, as the importance of data is transitioning from legacy, centralised systems to more decentralised data-friendly workflows.
This has many benefits for businesses in terms of efficiency and improved communication between departments.
In larger companies with different departments, you need to be able to work quickly while gathering information from different places. Having a decentralised data team that is interspersed throughout the organisation in different departments allows team members to get closer to potential issues.
By putting data team members in such close proximity to the day-to-day workings of different departments allows them to come up with detailed solutions that are practical and relevant.
While not physically tangible, data products are pieces of data which are treated as their own entity. Most data products can stand alone in functionality and help to section off and organise an overall data strategy into smaller more manageable projects.
Having a delegated product manager that works close to the project is important for quick feedback and fast turnarounds. Sometimes this ‘feet-on-the-ground’ personnel approach takes priority over waiting for a data scientist to manage the product; as long as they are reliable and able to report accurately to the data team.
Because the majority of employees in most companies are not data scientists you need to be able to make data accessible. Having workflows, standard operating procedures and systems in place can help those less versed in data become proactive team members; making them a valuable addition to the data team even if they don’t have data qualifications.
Highlight the importance of data during your hiring process to reduce friction later down the line. When hiring into a digital native culture look at the potential for someone to adapt to data-centric systems and operations.
They should also be aware of the vital role that data and feedback plays in improving business. By fostering a data native culture during the hiring process, it will become easier to ask for employees for help with data projects if required.
Making a business ‘data native’ is as much of a cultural change as it is a practical one. By integrating the importance of data into the hiring process and creating easy systems to follow, you have the potential to easily add extra manpower to the data team – without having to hire extra data scientists.
Having people on the ground helping the data team find issues through the lens of their own zone of genius is more efficient, more economical, and most importantly more effective.