October 1, 2021
Author: Eric Wong, Customer Success Lead, IBM Australia and New Zealand
It wasn’t all smooth sailing for our client.
A 2021 RMIT Online study by Deloitte Access Economics confirms what many of us know from experience – that data science is one of Australia’s most in-demand skill areas. What’s more, the employers surveyed by Deloitte reported their biggest skills gap was in data analysis – that is, they don’t have “the skill level required or skill is out of date”.
A few years back this client brought in a team of data scientists for a machine learning project. This was exciting, given the shortage of data science talent.
Its first goal was to improve market supervision, the data monitoring process that plays a vital role in helping to mitigate the risk of fraud to financial services companies and their customers.
But developing machine learning models without the right tools is difficult and time-consuming. The team worked hard but progressed slowly – until it deployed IBM Cloud Pak for Data early in 2021.
Transform how data scientists work
An IBM customer success manager was appointed to lead the project and liaise with various IBM experts to get the solution up and running. This included every aspect of deployment, from an IBM Power System AC922 server for accelerated data analytics performance, to IBM Cognos Analytics for data visualisations.
The solution also included IBM Watson Studio and IBM Watson Machine Learning. Together this holistic platform could ingest, cleanse, shape and analyse data, making it much easier to create and train machine learning models. Meanwhile, a team of IBM experts was available to help the client’s data scientists learn how to apply analytics and machine learning on the new platform.
Close the skills gap with an engaged team
As a result, the client’s data scientists now spend far less time on the grind of integrating and cleaning up data from multiple sources, so they are much more productive. Even less experienced data scientists have still been able to quickly get up to speed and deliver results.
Perhaps most importantly, the data scientists are highly engaged. They now spend more time on the most rewarding part of their job: breaking new ground with machine learning and coming up with solutions. Given the shortage of their skillset in Australia, their engagement and retention is critical.
Numerous studies by the Harvard Business Review and others have shown that technology’s role in employee engagement has become even more important as we shift into the hybrid work era. And this is especially vital for those employees driving transformative technologies such as data analytics and machine learning.
Fast-forward to a new use case
This project is just one example of what’s possible. Having struggled to progress its machine learning project for nearly two years, it’s already seeing improved results from its new market surveillance platform. Its data scientists are excited about the future and that has given the company the confidence to bring forward a new use case for machine learning: compliance.
For this new project, our client is using natural language processing for advanced analysis of all customer feedback, enabling it to streamline its customer-related compliance needs.
Invest in success
None of these advancements would have been possible without the right technology. But having the right teams supporting the company was also vital. Our IBM team, led by the Customer Success Manager, has not only helped our client accelerate what was a complex deployment, but we’ve also ensured the platform has the high levels of security that financial services companies require.
I love the title Customer Success Manager. Doesn’t it say it all?
As the lead of IBM A/NZ’s Customer Success team, I hear from clients that IBM’s investment in these roles is unusual, and a gamechanger. We aim to make every step of the journey easier for clients, so that they can get to success, and get there faster.
Every day I see firsthand how advanced technologies such as machine learning are helping to solve our clients’ business problems. I’m proud that we help clients set up for long term success in so many ways – and that we’re doing our bit to bridge the skills gap in data science. We’re helping clients attract top talent and then retain that talent with modern tools that allow them to do their best work. What could be better than making someone’s working day better, more satisfying?
Want to discuss how we can help you and your data science team? Connect with me here