Russ Pearlman's Blog

Executives from several major media companies testified before the Federal Trade Commission about the need for fees, taxes or tax credits for content being spread or aggregated across the Internet. The basic problem is that in the rush to get professionally published (i.e., newspapers) content on the Web, these companies decided to start doing it for free, hoping that advertising on the web sites would keep pace with what they were seeing traditionally in the print forms. These publishers have now learned, however, that on-line advertizing is a lot less lucrative – and with the switch from most people getting their news from “traditional” media to “Web 2.0 media”.

So, what is a major media company to do? Implement subscription models like the Wall Street Journal to fuel your success? Create premium member areas like ESPN.com or RushLimbaugh.com? Charge syndication fees to aggregators? Enforce copyright?

How about ask the government to give you tax credits to help defray your costs under the guise that our country needs a “free professional press”?

Within Digital Content Services at Capgemini, we have a pillar around Digital Monetization that helps to address these types of issues. While it’s a pipe dream that the US Government is going to be the ultimate savior here, major media companies need to figure out how best to fit within the new world of Web 2.0 and digital content. It’s no surprise that digital content is seen as less valuable than it’s physical counter-part (we’ve seen this in music, video, games and books). But, I think the biggest mistake an organization can make is to take old process and old ways of doing business and just try to apply the Internet.

When I buy a digital book on my Kindle, it’s just a digital version of something I could buy on paper.  They charge me $9.99 instead of $25 – so I’m happy. But, if they were to make the experience better – for example augmenting it with animations, providing extra features, or automatically making updates to non-fiction materials, I’d be willing to pay a more. But, that would take a new mind set and would require a whole new set of digital supply chain processes. So, Amazon would need to figure out which model it wants – one where revnue (and probably costs) are lower or when where revenue (and probably costs) are higher.

Or, perhaps, we can ask the US Government to provide a tax credit for Amazon selling digital books.

I’m proud to introduce an excerpt from one of Capgemini’s most recent point of views: “Video Gaming: The Next Level”. If you are interested in downloading the whole paper, please go here. (Registration required.)

The video game industry in the U.S. grew nearly 65% from 2006-2008, driven primarily by the newest generation of gaming devices, including consoles and portables, and a proliferation of successful titles, particularly key franchises such as Grand Theft Auto, Mario and Halo.

During that span, the innovation of the Wii dominated mainstream news. Today, headlines hail the iPhone as the next growth platform in gaming. Lost, however, in the focus on game play, form factor and motion controllers is a fundamental technological transformation that will reshape the industry: the connected gaming device, which we define as a device with the ability to download and manage entertainment titles.

Today’s gaming devices all boast connectivity, from consoles that join existing home networks to portables that use Wi-Fi to Smartphones that leverage global cellular networks. The original Xbox and PlayStation 2 were the first connected consoles; their next-generation counterparts matured the offering by tapping into Web 2.0 interconnectivity similar to that of Facebook and Twitter, creating social networks of their own. Since their respective launches, Nintendo’s DS and Sony’s PSP brought Wi-Fi connectivity to the portable gaming market. Historically, games have played a minor role in the mobile phone industry. Now sophisticated games are a differentiator in Smartphones, with the iPhone leading the way while Blackberry, Android and Nokia’s N-Gage 2.0 jockey to compete. Today’s devices are at varying stages of both connectivity and monetizing from
this connectivity.

This technological transformation arrives at a time when consumer behavior has become increasingly complex due to the rise of personalization and participation. Today’s consumers are increasingly interested in personalizing their gaming experience via unique avatars and user profiles. Their desire to participate with games is twofold: 1) to augment content and 2) to interact with other players. Gaming consumers seek to enhance and contribute to titles with user-generated content (i.e., skins and level editing) and developer interaction that influences the product itself. Consumers also desire to interact with each other via online gaming communities.

Maturing the connected technology will allow firms to meet the needs of this increasingly sophisticated consumer. Our View: Connectivity Changes the Game The proliferation of connected devices fundamentally changes the gaming  landscape. Traditionally, consumers have purchased video games via retail outlets in boxed format. While this remains the case today for AAA titles on consoles, connectivity threatens this model. 

John Marmaduke’s post about Redbox is a good one.

For those of you not keeping up, Redbox is a company that went out and bought a bunch of old vending machines and started putting DVDs in them for rental at grocery stores, department stores, hospitals, etc. The automated rental machine just takes a credit card, and charges a very nominal fee for rental.

Marmaduke argues that ‘giving away’ DVD’s at a $1 rental price for products that take hundreds of millions of dollars to produce is an unsustainable business model. Of course, he’s right! As he points out, newspapers have been giving away content on-line for years now, and they are dealing with the consequences – declining revenue and even bankruptcy.

There is a similar parallel in the video gaming industry. The cost of making games is going up, but there is a downward pressure on sales price. Along side the fact that many games are now going digital, there is additional pressure to lower price since consumers don’t value ‘virtual’ product the same as ‘physical’ product.

Personally, I think putting your head in the sand isn’t the right answer. Consumers will likely make trade offs when considering a $30 BluRay purchase vs. a $1/day rental. Perhaps they won’t get AAA content, but they will settle for lower quality (in terms of product and viewing quality). And, if Redbox isn’t the company behind a $1/day rental, someone else is certainly going to jump in and offer something as well.

The industry needs to attack the problem from both ends – finding ways to lower production costs, finding ways to be more efficient in supply chains (both physical and digital) and formulating new monetary models (i.e., micro transactions, subscriptions, etc.)

Earlier this week, Adobe announced that they are acquiring Omniture for $1.8b. For those of you unaware of the broad suite of solutions available from Adobe, it’s probably worth looking at their suite of offerings. At the highest level, Adobe provides a number of products for the creation of media & content from their suite of photo & video editing tools as well as their document creation and management tools. Additionally, Adobe plays heavily in the rich media presentation space with Flash and Acrobat. They have also made plays into the middleware space with Adobe Lifecycle, a fairly robust workflow management suite of tools.

Adding Omniture to their stack is actually a pretty natural fit. As the graphic from their web site (and reproduced on this blog) shows, there is a major opportunity to tracking and ‘understanding’ consumer behavior. Traditionally, this has been accomplished by logging user actions against typical HTML objects and trying to understand usage scenarios. But, with the advent of AJAX, Flash and richer delivery platforms, it’s become more complex. By incorporating Omniture side-by-side with Adobe’s Flash technology, there is an opportunity to make this simpler.

Of course, this all sounds great on paper. I think the biggest challenge is going to be organizational. Omniture works and thinks very differently from Adobe. And, the creative types (i.e., Flex / Flash) and analytical types tend to think about problems quite differently.

With last night’s game the official kick-off of the NFL season for 2009/2010, I can’t help but be excited. First, I’m excited because I’m an avid Dallas Cowboys fan. Second, I’ve made a new pledge to work-out during the games (trying to get healthy) – so I have no excuses. And, third, because Fantasy Football is just so darn fun!

There are very few iPhone apps that I’m willing to pay for, and even fewer that I’m willing to spend more than $0.99 on. But, the EPSN Fantasy Football application for $4.99 is on my list. So, not only is the NFL huge for national broadcasters but it’s also lucrative for DirectTV (NFL Sunday Ticket) and fantasy sites such as ESPN.

So, go out and enjoy – afterall, that’s what M&E is all about.

Nice article from Dean Takahashi from GamesBeat following a speech from Rich Hilleman, Chief Creative Officer for Electronic Arts. One part to really focus on: “… Hilleman talked about the changes he has seen in more than 25 years at EA, which he joined as employee No. 39 in 1983. The audience is moving beyond males. The platforms are becoming mobile, social and online-connected. And the play style is moving from hardcore to casual. The business models are in flux as well.” (Emphasis is mine.)

It’s no surprise to anyone who has been engaged in the video game business that change is afoot, but I think the difference between “change” and “flux” is that change is directed, flux isn’t.

Interactive entertainment is quite different than non-interactive – watching a movie on a small screen, on a large screen, etc. is still fundamentally the same experience – it’s just different levels of quality. Not to belittle that, but playing a video game on a small device vs. a large device is fundamentally different. I think the same thing holds true for the connected entertainment device – playing a game against the computer vs. others is a very different experience. Additionally, the opportunity to dynamically add in more content is different – while you can download additional episodes of a TV show, it’s still a serial experience. Interactive is user driven – so adding in new content is more fundamental to enhancing the experience (or completely changing it).

So, while I see “change” in the industry related to video, music and books, I see “flux” in the video gaming space. I see a dramatic opportunity over the next few years to totally transform the experience from the 1983 video game idea (albeit higher quality graphics, physics and audio) of today towards a more immerse, connected, dynamic and growing experience for tomorrow. Just like the Internet opening opportunities for emergent companies to take hold (think Amazon, EBay and others) it also opens up a lot of competition and ways to expand revenue.

I can’t wait…

• First In First Out (FIFO) – the idea here is that items get processed in order – the first request is the first to get processed; this is exactly like the line at McDonald’s or just about anywhere else you go. The problem with this approach is that it doesn’t take priority into account.
• Round Robin – this approach works when there are multiple queues, you pull one item from one queue, one from the next queue, etc. For priority, you can use this approach by having a ‘high priority’ queue and a ‘low priority’ queue; this way, both will get serviced over time. Since I travel a lot, I know of a good example of this one: the ‘first class’ line at the airport. Agents typically service someone from the regular line then someone from the first class line then regular then first class and on and on. This approach works fairly well in helping to assign priority, but it’s still doesn’t discriminate between levels of priority, and it can cause a backlog of priority jobs that don’t get serviced in time.
• Priority based – this is an ‘enhanced’ round robin approach. In this case, you assign a priority amount to each work item. Each item in the queue is then sorted based on priority so that the ‘most’ urgent requests get serviced first. Again, using the airport example, this is how airline employees are treated – they get to move to the front of the ‘first class’ line when going through security – ahead of the elite travelers.
• Shorted Job First – this approach sorts jobs based on what can be completed the quickest. It ignores priority, but it does tend to optimize the system so that you can get the most jobs completed over a period of time. By way of analogy, think about standing in line for a copy machine. If 10 people have 1 page to copy and 1 person has 100 pages to copy, it’s most efficient to let the 10 people go first. The problem with this approach, though, is that as more work items come onto the queue, it’s possible that long running processes get pushed back so far that they never get done – essentially aging out.
• Multi-Level Feedback Queues – this approach uses a number of queues which take into account both processing time as well as priority. It can also take aging into account to make sure that a low priority, large job eventually does get completed as its age eventually makes it high enough priority.

As I’ve continued to approach various digital supply chain problems, I’ve been continuously reminded that most of these problems have been seen before in various other contexts. It’s a good idea to make sure that you don’t re-invent the wheel – if there is a good algorithm or approach already being used, leverage it…

In a discussion yesterday with a client, we discussed some bleeding edge concepts around the Internet – they insisted on calling this Web 3.0.

Tim O’Reilly, innovator of the term Web 2.0, has already staked some ground on that term, however. Web 1.0, according to O’Reilly, was the first generation of the web for Internet sites, basic e-commerce, B2C, B2B, etc. It gave rise to several giants including Amazon, EBay, Google and others. Then – the bust… Following that time, O’Reilly sponsored a conference entitled “Web 2.0″ – it was more about the resurgence of Web 1.0,  but it quickly took on a whole new term as C2C, social networking and a new slew of technologies (e.g., AJAX) hit the scenes.

So, then, what is Web 3.0? Canonically, Web 3.0 can be thought of as the ‘semantic web.’ In Web 1.0 and Web 2.0, there is data, there are transactions and there are SILOS. Does Facebook know what’s happening on other sites? Does Amazon.com integrate with your iTunes account to provide recommendations? In a Web 3.0 world, that can all be broken down.

I think some of the first foundational pieces of Web 3.0 are showing. Microsoft announced that Facebook and Twitter will be available from within the XBox 360 console. Not integrated, mind you, but a step. And, Facebook’s recent announcement of  buying FriendFeed is another good example. On the technology front, things like RDF and cloud computing will become common.

I know I’m excited… But, as the client and a collegue pointed out – what about privacy issues? Oops. The human factor may get in the way.

I’ve been reading Brain Rules by John Medina, and I can’t recommend it enough. It covers John’s 12 brain rules (from exercise, to sleep to stress, etc.) that you should really consider as part of your daily life.

By way of background, I originally wanted to become a neurologist when I went to college. My undergraduate degree was in Neuroethology mixed with a minor in Psychology. Go ahead, look up neuroethology, I’ll wait   Actually, don’t look it up – I can sum it up as basically understanding behavior based on the way you are wired. So, John’s book smacks right into the type of stuff I really was interested in.

When I learned that biology wasn’t really my cup of tea, I then went into computer science and got my master’s degree in neural networking / artificial intelligence. It turns out, you can mimic a lot of what I learned in neuroethology for patterns of intelligent computer processing (see my blog post below about the use of genetic algorithms in supply chain planning as an example).

It turns out, that you can apply a lot of this same learning to people. And that’s exactly what brain rules set out to do. I hope you enjoy it…

Back when I was running the development studio for Koios Works, I was in charge of building out the AI for our games. At first, we built some fairly straight forward approaches to planning, but the AI ended up being so scripted that replay of game levels just wasn’t fun. (Sound familiar?) For our second title, we did a major upgrade of our graphics engine, and in parallel, we decided to do a major upgrade of our AI.

We ended up selecting a genetic algorithm that essentially understands ‘good behavior’ vs. ‘bad behavior’ in selecting a ‘good’ solution to the problem being presented. For games, this is a fairly straight-forward problem – decide on the best move against the human adversary following the rules of the game. It did this based on an ‘evaluation function’ that is able to numerically rate a proposed solution.

The algorithm itself then simulates a genetic evolution to match up the very best solutions found to, hopefully, generate the next generation of even better solutions. (The details are somewhat too complex to describe here, but generally, you just need to focus on creating an evaluation that is able to rate options – all the hard work and intelligence is already coded into the algorithm itself.) In the end, our AI was considered among the very best developed for war-games (at least based on feedback from players in that fairly niche area).

To help bring in additional revenues during that time, I was also doing some outside consulting work. And, we were able to apply the same AI approach to a ship scheduling (i.e., supply chain) problem for the petroleum industry. The reason why you use this type of algorithm is that it is able to develop approximations of a great solution in a short amount of time while still being flexible to appreciate new variations to the problem (for example, the customer is this case was able to add in new ships or new pickup opportunities to perform what-if analysis – as well as insert new rules about profitability vs. customer satisfaction, etc.)

What got me thinking about this recently was some work we are doing for a client in the areas of digital supply chain. Just like the real world, when you are doing content processing from step-to-step, there are some real resource constraints that you should be aware of. From a human perspective, you have to balance the use of QC resources, touch-points for approvals, manual tasks (such as encoding a video or other master material into digital form), financial approvals, etc. On the computing side, you are potentially talking about huge amounts of disk and CPU resource utilization that can quickly translate into expensive infrastructure. To help optimize these resources, the application of AI is a great solution; and, a genetic algorithm specifically, is a nice fit to the problem since it can so easily be expanded with new influencers as well as adopt to variations in the type of content being processed (i.e., music vs. video vs. gaming, etc.)

So, while the emerging area of digital supply chains has different issues than traditional supply chain problems, let’s not forget to incorporate the lessons learned and optimization approaches that we’ve relied on for years.