What's in this podcast?

In this episode, Jason talks to Jeremie Jakubowicz, the Vice-President of Data at ManoMano about the use of data in making predictions, and its integral role in artificial intelligence. ManoMano is currently the largest gardening and DIY online marketplace in Europe.

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.

What are your thoughts on this topic? We’d love to hear from you; join the #HubandSpoken discussion and let us know on Twitter and LinkedIn.

For more on data, take a look at the webinars and events that we have lined up for you.


One Big Message

While it might seem like a daunting task to create smaller data points along the chain, doing so will allow you to see exactly where things are going right – or wrong. If you’re only relying on the data for the end result, you won’t be able to optimise as effectively.

[00:27] Jeremie’s background from academia into corporate data

[04:50] What ManoMano does and how they use data in their everyday operations

[06:30] The role data has played in ManoMano, and how it became a data-native business

[11:30] Incorporating a cultural change and finding the balance between being prepared and launching

[16:00] Going over various data and AI use cases at ManoMano including search engines, automation, communicating with suppliers

[22:30] Use of data to predict buyer behaviour

[33:10] The two fundamentals of building a strong data foundation for your business


Take advantage of every opportunity while learning

It’s important to take advantage of every opportunity that may arise. Learning can come in many different forms and should never be ignored, even if it seems trivial or unrelated to your current area of study – you never know when you might need the knowledge gained.

There are countless examples where gaining knowledge and experience outside one’s major has helped people shape a better career trajectory for themselves. This is especially important in the field of data where many people usually come from other academic backgrounds due to the historical lack of pure data courses available. It wasn’t until about a decade ago you could study a data science course at a tertiary level. As the field of data has grown within the past few decades, so has its importance in academia and tertiary studies.


Personalising data for the end user

Personalisation has become a buzzword in the tech industry. One of the most common ways to personalise your experience is through data. Data can be used to create an immersive and tailored user experience by knowing what you are interested in, how much time you spend on different pages or what you like to purchase online.

Benefits of personalisation are that it creates new experiences, saves time for consumers and makes companies more efficient. In fact, it is so omnipresent that personalisation is now expected as the new normal by technology users.


Data for automation vs. data for decision-making

Data for automation has several benefits that include: increased efficiency and less human error. These systems are complex and can facilitate easy communication between the customer and marketplace or between the suppliers and the marketplace.

Even more complex systems are required to make decisions. Many people rely on data-guided decisions everyday to help them make their choices, to give them confidence about what they choose. Decision-making data platforms need to be able to self-regulate and adjust as necessary based on many different data points, making them incredibly intricate.


Build a strong foundation

In order to create a solid data strategy for your organisation, research and invest in two things: a tech stack capable of growing with your business, and in-depth knowledge of the business and its goals.

Integrating data requires a cultural change because an organisation needs a holistic understanding of how data flows through their system. This means that everyone needs to be on board and willing to communicate with each other. If departments don’t communicate their findings and results then you will be missing out on golden opportunities for improvement.


To summarise

Creating a scalable data-driven business is easily achievable if you start with the right technology and implement the correct systems from the very beginning. Having scalable systems will allow your business to grow, adapt and implement as necessary without putting strain on other data systems.

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