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September saw the SP team attend two shows and they couldn’t have been more worlds apart. Like most of my peers, the second weekend of September was taken up with the regular industry fixture that is IBC. As always, it was an enjoyable and busy weekend speaking to customers and helping them plan their technology investments, catching up with friends and getting the industry gossip and finding out what the technology roadmaps look like for the leading vendors. It was a good show but, in hindsight, it felt a little bit like Groundhog Day when it came to talking about the future of technology in the M&E space…

Fast forward a week and I was sat in a conference hall in San Francisco (that had been bemusingly decked out as a national park) watching Lars Ulrich from Metallica wax lyrical about how Salesforce has changed how the band are engaging with their fans and generating new revenue streams … This is Dreamforce the annual Salesforce conference where 170,000 people from varying industries descend on San Francisco to talk about the direction of technology.

The thing about Dreamforce is that while it is effectively a big sales pitch for the Salesforce platform, the technology and discussions that are being had are not only inspiring but enlightening. Having a week to take off the blinkers of the M&E space and soak up what is happening in other industries really brought home exactly why I joined Support Partners. However, this wasn’t Harry (CEO) and Pete’s (COO) first Rodeo – they have been attending Dreamforce and other non-industry shows for a while and in doing so have shifted the way of thinking of not only our staff, but our clients … making SP a rather unique entity in the M&E space.

The conversations at the two shows could not be more different whilst still speaking about the same topic.

I found that a common conversation at IBC was around how vendors are utilising ‘AI’. Every man and his dog had integrated ‘AI’ into their product it seems. When you delve into what this actually means it’s effectively an integration between their product and one of the big 4’s machine learning API’s (Google, AWS, MSoft, IBM). In most cases, they are using the API to enrich the metadata of the content their product is processing – whether by using computer vision or speech to text. OK, cool. This is super useful as we all know that most media companies are sat on a tonne of content that has little to no metadata associated with it, but is this actually AI? No. This is machine learning because at no point is the algorithm giving the end user a suggestion or actionable insight to help augment the end users ability to do their job.

At Dreamforce, however, this was definitely not the case. The application of AI has moved beyond metadata enrichment to how do you take all available datasets and connect them to break down business silos, improve operational efficiency and give a seamless end user experience. My favourite case study to highlight this 360 approach was at the Mulesoft (a recently acquired integration platform) keynote where we saw how predictive analytics and trackable assets were being leveraged in the automotive industry to change how the supply chain is managed. Using integrations and a trackable asset, they combined different data sets to automate the provisioning and tracking of parts and the interaction with the franchise, the supplier and the end customers. Predictive analytics enabled the system to make smart choices on part recommendations based on factors based on delivery time, cost and reliability. This case study was so apt that it felt like an analogy for the conversations and PoC’s we are undergoing with our client base.

A 360 approach needs to be embraced by our industry

In short, IBC has shown that if end users start using machine learning tools in angst they will soon have a deluge of data which will be useful when trying to search for content in their asset management system but pretty useless when trying to get business insights. This is where a 360 approach needs to be embraced by our industry. Organisations of all sizes need to be having the conversation about how to connect data from disparate systems (metadata enrichment being only one) and how to apply true AI/Predictive Analytics to these datasets to make objective decisions on operational change. Only then will we be in a position where we are using AI to drive business efficiencies.

If you have the chance to attend a show outside of the traditional industry mainstays then go to something like Dreamforce, AWS re:invent, MSofts Ignite because technology is moving fast, faster than I think a lot of people realise in the M&E space.