Head of Big Data and Advanced Analytics
Recently I was asked to speak at CogX19, one of the largest AI events in the UK.
With an agenda spread across 600 speakers, 10 stages and three days, it was clear to see that AI is now touching every industry and continues to grow in importance.
I spoke alongside Dr Athina Kanioura, Chief Analytics Officer and Global Lead of Accenture AI, a global leader I admire and have known for a very long time.
We discussed how Vodafone Business is using Big Data and AI to generate value, and (hopefully) imparted some useful points to the crowd.
A key question with projects in this field is “how do I begin?” - So I wanted to share some thoughts on my work at Vodafone Business to spark ideas and discussion.
How we started our AI journey at Vodafone Business
As you might have guessed, creating a data strategy for a company that operates in 25 countries is not a simple task.
You first need to understand how the company works; the relationship between the operating markets and the challenges they face when it comes to data and advanced analytics.
You also need to understand these challenges from the perspective of a specific business area - for example, the challenges that the commercial or finance team faces.
And before deciding on a strategy, it is crucial to have the right technological landscape in place (Big Data on prem and/or cloud), good quality data, a reliable data governance program and the bandwidth to cope with the complexity and sophistication needed around data and AI. This includes insourcing skills that are at times scarce in the market.
Finally, you need to get commitment from across the business – as I have mentioned before, for big data and AI to be a success it needs to be everyone’s job, not any one team.
This means that you must demonstrate several compelling use cases that motivate your stakeholders.
For Vodafone Business, it was crucial to agree a strategy that not only supported the organisation but also aided our customers in their own digital transformation journeys. Businesses today recognise the need to gain insight from their data and they value a partner who can advise from experience.
To demonstrate real value, big data needs to be scalable
Once the strategy is decided, there is little point in creating a use case that will only benefit a few customers or a handful of colleagues. You need to identify a scenario that is rapidly scalable in a short time frame, making a real impact to the business.
However, sometimes even data scientists cannot truly understand the value that a use case can deliver in isolation, or appreciate where it can be amplified.
That is why an organisation must be united in its commitment to the potential of data: then it can, as one, identify opportunities where it can be most effective and therefore ultimately, make real progress and transform as an organisation.
Once started, how do you succeed on your AI journey?
Even when you identify what you can do with data insight, sometimes it is not enough. The solution may seem obvious but it can be challenging as the data you need is not always available, may not be complete or have quality problems.
That is why in some cases we work with strategic partners, such as Accenture, to improve on our strategy and to gain specific expertise and support.
It’s important to acknowledge that in today’s environment no one company alone can be great at everything – we need to form strong relationships to truly grow.
The rapid availability of data from new technologies means that all businesses need to create a practical strategy around big data and AI; otherwise, they risk being overtaken by their competitors.
If you can demonstrate this clearly and motivate the business, then you are already well on the way in your AI journey. And looking at the huge variety of industries, experts and topics at this event alone one thing is clear; this is just the beginning.
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