How will analytics change our world by 2020? – The

Games IndustryIAPA Brisbane Xmas event Dec 3 2014

Some background on this presentation

This is a presentation I gave at the IAPA (Institute of Analytics Professionals of Australia) meeting themed: How will analytics change our world by 2020?

I and 3 other members, each spoke about our respective fields and we all joined in a panel discussion afterwards.

It was a whole lot of fun and both the presentations and discussion were really interesting.

You can find the IAPA here: http://www.iapa.org.au/

Some background on me….

What will the games industry look like in 2020?

I think the industry stays like it is today but the volume gets turned up.The three current trends that I think will be key are:

1. All games types open to everyone to make & update

2. Games As A Service

3. Content platforms become more important than technology platforms

What will the games industry look like in 2020?

All games types open to everyone to make & update

New, powerful devices bringing AAA experiences to every developer/makerSoftware & cloud services are bringing advanced capabilities to the market at a price point low enough for that not to be a hurdle for anyone.

App stores and the plummeting cost of transmitting & storing data means everyone can provide regular content updates

What will the games industry look like in 2020?

Games As A Service

Games are content channels you go to regularly to consume new content. This is already the case for many games now.

Content will be customised for geographical regions and for social groupings

Games will adapt their content based on what you do and based on who you are. This will guarantee a rewarding experience rather than just promise it like television & movies do now.

What will the games industry look like in 2020?

Content platforms become more important than technology platforms

Previously games were locked to technology platforms. Today games allow users to move their playing data across multiple devices & platforms.

Content platforms (Kakao, Facebook, LINE) are able to serve their users tightly integrated social & gaming experiences. They are the new television networks.

Content platforms wield the power of access to users. Expect to see content channels have exclusive games.

Will data sharing be part of every aspect of day-to-day life?In games, data sharing has been part of day-to-day life for quite a while.

Meaningful, collaborative, gaming experiences are the gold standard in data sharing. Great games do this now.

I expect more & more games to head in this direction and for games to show how to monetise from this in ways that are delightful and helpful for the players rather than exploitive.

What implications will greater data streams have for analytics?Data volume already exceeds our ability to extract value from all of it. Future volume increases will force us to throw data away.The sooner you take action on player data better you are of responding to the player in a way that resonates with them.

More powerful devices won’t allow more on-device data processing. In fact they’ll contribute to the data volume.

Expanded capabilities means more data the device can send back about the player’s experiences and the player themselves.

What implications will greater data streams have for analytics?In memory processing will allow us to leverage close-to-real-time data streams for reactive content changes.

Players will want reactive content experiences on native mobile/device apps.

Predictive analytics and machine learning tools will focus less on prediction and more on reactive server side data cleaning & aggregation.

How should analytics professionals prepare for this new world?“Raw Data” is an oxymoron.

The formation of game data, even the most basic data, contains a lot of nuance. Analysts need to understand intimately the way in which the games, devices and processing technologies produce the data.

New ways of game outputs and inputs (like VR headsets) will add invisible layers of complexity.

How should analytics professionals prepare for this new world?Predictive analytics and machine learning tools will become common place as a way to deal with the large volume of data.

Analysts will need to be able to leverage these tools in their day to day jobs.

Experimentation is able to be automated across a network of connected devices so becomes available, at scale, to almost anyone for the first time ever.

There will be a huge demand for analysts with the grounding in the scientific method to properly take advantage of this.

Thanks for listening

Thanks for taking the time to view my presentation.

I encourage you to leave any feedback you might have.

You can find me at

Linkedin http://au.linkedin.com/in/andrewsaul7

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