As part of this year’s Social Media Week, I’ll be hosting one of the sessions at a free one-day event held at SAP Palo Alto on February 15th. It’s entitled “Social Business: Designing Social into Products”, and I will be accompanied by guests including Lisa Joy Rosner, Chief Marketing Officer at NetBase, Dave Brockington, in charge of Product Management & Strategy for SAP’s collaborative decision-making product, StreamWork, and others I’m still trying to confirm. Please join us by registering for the session or join via online streaming on the SAP Facebook page, and the hashtag for the event is #SMW12

In this post, I’d like to share some ideas about why I believe that there are now fantastic new opportunities to improve all kinds of products using social media techniques.

PLEASE GIVE YOUR FEEDBACK. This blog post and the session I’ll be hosting are also “products”, in a sense, and I’d like to use the techniques outlined below to make them as good as possible: please post your feedback and any answers you have to the questions below, or suggestions for great panelists, and I’ll use that feedback to improve the session above!

Introduction

I believe that we’re still in the era of a “horseless carriage” version of social media: we added a motor, but kept the rest of the carriage.

In other words, while we understand how the new technologies work, we’re still tending to bolt the new social techniques onto our existing processes, rather than fundamentally rethinking those processes in the light of the new opportunities.

This tends to be true of all new technologies, of course. But for some reason there seems to be a bigger gap than usual – perhaps it is because the “trees” are so obvious (social media analytics, enterprise collaboration, etc.) that they tend to obscure the “wood”: the opportunity to sweep away existing bottlenecks in our business processes.

Social media is too often a marginal activity that people are happy to leave up to a dedicated team elsewhere in the organization, rather than embedded in everything we do. This post looks in particular at how social media techniques can be applied to the process of product creation.

Social / Product Trends

Why introduce something new? Why can’t we just keep doing what we’re doing today? Let’s start with some of the background trends:

Transparency: Whether you have a great product or an awful one, prospective customers can get the information they need directly from unbiased peers. This means that traditional product sales and marketing is being marginalized, and that core product quality becomes even more fundamental.

A great product – one that customers are delighted to own and use, and talk about to other people – can now take off at lighting speed, with almost no promotional cost. And news about product problems or poor service can spread even faster. The good news is that product creators can communicate with their customers more cheaply than ever: we may be naked, but we have a megaphone. It has to be used wisely. Honesty and credibility are essential values when talking about your products to the market.

Direct Contact With Customers: In large product organizations, there’s often a big communications gap between the people creating products and the people using them. The creators and designers of software, for example, have typically had to rely on other people to research the needs of potential users. The researchers then pass on that information in the form of “consumer profiles”, “personas”, or “ethnographic research”, which is used as a basis for creation. Something often gets lost in the translation, but is often seen as the only feasible way to operate.

Software engineers (for example), frustrated by this limited visibility, complain how hard it is to get access to customers, who are often protectively fenced off by sales teams (perhaps worried that developers might let too much of the truth slip out about product bugs or delays).

The advances of social media means all this can now change: vast numbers of potential users are only a few mouse-clicks away, participating in industry forums, complaining about alternative products, or talking about their favorite features.

Network Leverage: There are now socially-enabled running shoes, socially-enabled cameras, socially-enabled toys, and socially-enabled enterprise software. Almost any product can now be “social”, and hence experience network effects that may outweigh the other product features.

Extended Ecosystems:By embedding more use of social techniques into product creation and selling, we’re inevitably creating more complex, interactive networks of ecosystems around our products, with customers, partners, suppliers of social networking, etc.

How do “Social” and “Product” Interact?

I believe there are three main ways in which we can create new or better products through social media techniques. It’s clear, however, that there is still a lot to learn before these techniques become commonplace — in each section, I’ve added some of the questions I believe need to be addressed: again, any feedback you have is more than welcome!

Social-improved products

First and most obviously we can use social media to improve the way we create existing products. New techniques include:

Social Research. It’s now easy to find data about new opportunities, such as customers complaining about business problems or competitor products. And it’s easy to get customer feedback on problems with our own products. Given the potential for better products, I believe we should be investing extensively in these new areas. Questions:

• What valuable data is available now that wasn’t before?
• What are the costs and opportunities associated with these new techniques?
• How much time should product creators spend communicating with communities vs. creating products?
• How do systems have to change to ensure that this type of research is consistently integrated into the product creation process?
• What are the real-life limitations of such research? i.e. what kinds of important data can we not get with these processes?
• What social research tools can we build into the product experience? (e.g. making it easy to invite others when using the product, and tracking success, or an online game maker tracking the price of different virtual weapons)

Ideation. One of the most painful parts of any product creation process is prioritization – we can never make a “perfect” product. There will always be some compromise in terms of functionality or cost. New ideation platforms, such as SAP’s Idea Place offer an opportunity to ask customers and potential customers to give their feedback directly on possible new features and what compromises to make.

These opportunities are not limited to software or technical products – consumer goods companies can run surveys on online forums, authors can ask online discussion boards for plot ideas for their next book, etc. This gets us closer to “crowdsourcing” the creation and improvement of products. Questions:

• When is ideation not appropriate?
• What types of products and features work best for ideation?
• How can we motivate our customers and prospects to participate?
• What level of transparency is appropriate?
• How do we handle rejection of non-chosen products and features?
• What are the dangers of competitors seeing the data, or gaming the results?

Social Prototyping. Basic ideation isn’t enough. I’m sure we can all think of an experience where we didn’t realize we wanted or needed a particular product until we tried it out. Product designers, after all, can have great ideas of their own, based on their deep market knowledge. One key problem today is that somebody in a company may what they believe is a fantastic idea for a new and different product. But in order to pursue the product, they need resources and permission of several layers of management.

Those managers may not have any real frame of reference to determine if the new product is a real opportunity or not, and may not be incented to take any risks. This can result in some combination of dissatisfied product creators (if the idea is rejected), wasted time (slow decision-making at each level ), or wasted money (if the idea is accepted, but the product fails). But using social media, it’s now much easier to create fast prototypes (mockups, concept version, wireframes, etc.), and then make them available to customers for testing and feedback.

The benefit is that it’s much clearer whether a product really does appeal to customers or not, helping the prioritization process. The car industry has long done this with “concept cars”, and SAP has tested these techniques with through its SAP Research Prototyping group. Ideas such as integration with Google Maps were shown to be extremely popular (and so were rushed into production) while some ideas weren’t interesting (and the person proposing the new feature had a learning experience). Questions:

• How can we introduce more extensive prototyping and social feedback into our product creation processes?
• How do we decide if a prototype is successful enough to productize?
• Are there any other benefits to this type of process? (marketing, thought leadership, etc.?)
• Does this approach cost more or less than existing methods?

Social-Enabled Products

We can integrate social media into products to improve their usefulness or effectiveness. Games you can play with other people in your social network are more interesting that games you play on your own. Our devices are increasingly wired to be able to share information – you can buy applications and shoes that share information socially on platforms such as RunKeeper. Runners can use the social-enabled devices to share data with a coach, boast of their achievements, embarrass themselves into improving their times, or let relatives track where they are during a marathon. And if you’re logged into Facebook when you visit the site, it will tell you which of your friends are already using the products.

Hybrid cars can keep track of your fuel consumption, so you can compete with your friends about who is the most sustainable driver. Restaurant guides can give us information based on the ratings given by our friends and other restaurants we’ve visited on foursquare or “liked” on Facebook. Enterprise software vendors can build collaboration into existing business applications, letting people apply social media techniques to supply chain collaboration or track the progress of sales deals. Even Lego is becoming social.

• What are your favorite examples of social-enabled products?
• How important is social enablement compared to other features of a product?
• Do product creators have to be aware of new power-players in the social eco-system?
• What other products should include social but don’t today?
• What about the limits of social privacy when using such products?

New Products On Top of Social

There are opportunities to create new products “on top of” social networks, or as by-products of them. Companies such as LinkedIn have been able to create new “products” based on the data gathered in their networks, such as “Talent Match” or “Jobs You May Be Interested In”. New tools could help improve the success or failure of a big merger by analyzing the different social networks within the two organizations over time. Companies could develop more sophisticated “friends and family” offers for their products. Car-sharing services could leverage social networks to improve usage rates.

• What are some other good examples of leveraging social networks to create new products and services?
• Is this something that the rest of us even need to think about?

Conclusion

We’re a long way from “build it and they will come”, but we’re not yet at “come build it with us”. I look forward to your feedback!

Interested in Social Media? (and everybody should be, because these techniques are changing EVERY business process, not just marketing). Come and join us!

As part of this year’s Social Media Week, SAP Palo Alto will be hosting a free, day-long non-SAP-focused event on Wednesday, February 15th with a glittering array of industry experts discussing a variety of key social topics:

Just some of the participants: Maggie Fox, CEO of Social Media Group | Ray Wang, CEO of Constellations Research|Jonathan Becher, Chief Marketing Officer of SAP | Barbara Holzapfel, SVP & Managing Director of SAP | Rachel Happe of The Community Roundtable | Srini Tanikella, SCN community member |Kimarie Mathews of Wells Fargo | Deirdre Walsh of Jive Software | Brian Ellefritz, SAP Social Media Strategic Services | Lisa Joy Rosner, Chief Marketing Officer at NetBase |Dave Brockington, Product Marketing & Strategy, StreamWork | Me!

You are invited to attend on-site if you’re in Silicon Valley, but the sessions will also be available through online streaming on the SAP Facebook page.

I’ll be hosting the last session of the day, on Social Media and Products – more details about that session in a separate blog post: Social+Product=Better Products.

Please join us! Click on the links below to find out more and to sign up to attend one or more of the sessions (sorry, to attend the whole day, you have to sign up four times…)

SAP Social Media Day, Wednesday, February 15th

Location: 3410 Hillview Avenue, Building 1 Café, Palo Alto

Hashtags #SMW12 #SAP, and find event-related blogs on the SAP Community Network and SocialMediaWeek.org.

I presented at my first conference of the year last week, the Heliview Business Intelligence and Data Warehousing 2012 conference in ‘s Hertogenbosch, Netherlands.

The first keynote, by Erasmus scholar Dr. Roeland Dietvorst, was about “Performance Management in the Brain”, and a subject close to my heart: the (severe) limitations we evolved apes have when trying to make rational decisions. He illustrated his point with examples of great research that show that:

• Including “irrelevant” product choices can make big changes to preferences;
• Our emotional state has a big influence on what choices we make;
• Men shown pictures of attractive women tend to make worse financial decisions;
• etc

He also reviewed some of his own research, scanning the brains of sales people to see if there was a correlation between brain activity, competence in understanding other people’s state of mind, and selling skills. He finished by underlining that we have “two brains,” and that business intelligence can help us move decision making to our more rational, less emotional side.

I did the other morning keynote on “Real time enterprise from theory to practice”:

“The amount of information we face is growing by the day. Both volume and type of information. IT organizations not only incorporate customer or product data, but new sources such as location data and data streams from social media play a significant role. In addition, we want information available in the context in which we operate, and preferably independent of the site or device. To make this possible innovative solutions are needed that can work with large volumes of data. In-memory computing may by some be considered as not yet available but the reality is different. There are several examples where this is being successfully implemented and numerous organizations are achieving demonstrable benefit. This presentation shows that the real-time revolution has already started and how it’s being practiced today.”

The presentation reviews the state of the BI market and technology, and ends with some examples of companies using information to change the way they do business. As usual, here’s a copy of the slides, in Adobe PDF and Powerpoint PPTX format.

I’ll be in London next week presenting at the Gartner BI Summit 2012 — hope to see you there!

Update: here’s a nice write-up from the Dutch team about the event.

Last year, Ajay Ohri of the DecisionStats web site asked me to predict the top three analytic trends for 2011. He recently challenged me to score how well I did – here’s a copy of the post he put on his site, with the predictions and some comments on what actually happened during the year:

(1) Analytics, reinvented. New DW techniques make it possible to do sub-second, interactive analytics directly against row-level operational data. Now BI processes and interfaces need to be rethought and redesigned to make best use of this — notably by blurring the distinctions between the “design” and “consumption” phases of BI.

Score: 10. I spent most of 2011 talking about this theme at various conferences: how existing BI technology is rapidly becoming obsolete and how the changes are akin to the move from film to digital photography. Technology that has been around for many years (in-memory, column stores, datawarehouse appliances, etc.) came together to create exciting new opportunities and even generally-skeptical industry analysts put out press releases such as “Gartner Says Data Warehousing Reaching Its Most Significant Inflection Point Since Its Inception.” Some of the smaller BI vendors had been pushing in-memory analytics for years, but the general market started paying more attention when megavendors like SAP painted a long-term vision of in-memory becoming a core platform for applications, not just analytics. Database leader Oracle was forced to upgrade their in-memory messaging from “It’s a complete fantasy” to “we have that too”.

(2) Corporate and personal BI come together. The ability to mix corporate and personal data for quick, pragmatic analysis is a common business need. The typical solution to the problem — extracting and combining the data into a local data store (either Excel or a departmental data mart) — pleases users, but introduces duplication and extra costs and makes a mockery of information governance. 2011 will see the rise of systems that let individuals and departments load their data into personal spaces in the corporate environment, allowing pragmatic analytic flexibility without compromising security and governance.

Score: 6. The number of departmental “data discovery” initiatives continued to rise through 2011, but new tools do make it easier for business people to upload and manipulate their own information while using the corporate standards. 2012 will see more development of “enterprise data discovery” interfaces for casual users.

(3) The next generation of business applications. Where are the business applications designed to support what people really do all day, such as implementing this year’s strategy, launching new products, or acquiring another company? 2011 will see the first prototypes of people-focused, flexible, information-centric, and collaborative applications, bringing together the best of business intelligence, “enterprise 2.0”, and existing operational applications.

Score: 6. We didn’t see many of these in the traditional enterprise BI landscape, but 2011 did see the rise of sophisticated, user-centric mobile applications that combine data from corporate systems with GPS mapping and the ability to “take action”, such as mobile medical analytics for doctors or mobile beauty advisor applications, and collaborative BI started becoming a standard part of enterprise platforms.

And one that should happen, but probably won’t: (4) Intelligence = Information + PEOPLE. Successful analytics isn’t about technology — it’s about people, process, and culture. The biggest trend in 2011 should be organizations spending the majority of their efforts on user adoption rather than technical implementation.

Unsurprisingly, there was still high demand for presentations on why BI projects fail and how to implement BI competency centers.  The new architectures probably resulted in even more emphasis on technology than ever, while business peoples’ expectations skyrocketed, fueled by advances in the consumer world. The result was maybe even more dissatisfaction in the past, but we can hope that the benefits of the new architectures should start becoming clearer during 2012.

What surprised me the most:

The rapid enterprise rise of Hadoop / NoSQL. The potential of these technologies has always been impressive, but I was surprised just how quickly they have been used to address real-life business problems (beyond the “big web” companies where they originated), and how quickly it is becoming part of mainstream enterprise analytic architectures (e.g. Sybase IQ 15.4 includes native MapReduce APIs, Hadoop integration and federation, etc.)

Prediction for 2012 

I hope to do a longer post on this, but here’s my initial take:

As I sat down to gather my thoughts about BI in 2012, I quickly came up with the same long laundry list of BI topics as everybody else: in-memory, mobile, predictive, social, collaborative decision-making, data discovery, real-time, etc. etc.

All of these things are clearly important, and we’re going to continue to see great improvements this year. But I think that the real “next big thing” in BI is what I’m seeing when I talk to customers: they’re using these new opportunities not only to “improve analytics” but also fundamentally rethink some of their key business processes.

Instead of analytics being something that is used to monitor and eventually improve a business process, analytics is becoming a more fundamental part of the business process itself. One example is a large telco company that has transformed the way they attract customers: instead of laboriously creating a range of rate plans, promoting them, and analyzing the results, they now use analytics to automatically create hundreds of more complex, personalized rate plans. They then throw them out into the market, monitor in real time, and quickly cull any that aren’t successful. This kind of “analytics first” transformation has happened to other industries in the past, but the new technologies are helping more  industries and companies to do business in new ways that would have been inconceivable in the past.

I look forward to talking more about these themes at upcoming conferences this year, starting with Gartner Business Intelligence Summit 2012 in the UK next Monday — and hope to see you at one of them!

Mobile BI has been around for a long time. Starting in the late-1990s, the first SMS-enabled telephones became mainstream in Europe, with basic broadcasting of the latest figures available in your BI system (or email, fax, pager, etc.). By the end of the decade, the first telephones with WAP browsers were used to provide interactive BI, quickly followed by connected PDAs with basic HTML browsers.

Here’s what SAP BusinessObjects looked like on the Nokia 7110 in 1999, on a Compaq PDA running Windows Pocket IE, an AvantGo PDA, and a Japanese DoCoMo i-mode phone in 2001:

The arrival of all these new mobile devices was supposed to usher in a new dawn of mobile analytics. Here’s a slide from a presentation a decade ago by then-marketing-VP Dave Kellogg, including the heady prediction that “5-25% of companies indicated they already provide or will provide wireless access to BI within 6-12 months”.

Business Objects launched a big initiative to go after the mobile market, and managed to sell projects to customers including JP Morgan (Palm Pilots) and Zurich Insurance (a mobile extranet for risk managers).

But, clearly, the market didn’t take off – PDAs became more widely used, and phones got better, but they weren’t used much for BI. The user interfaces were too clunky and connection speeds were too slow. Interest in mobile BI did grow slowly over the decade, notably as RIM blackberry devices became ubiquitous, but it took the wide availability of 3G wireless and modern smartphones/tablets to provide truly usable interfaces.

Finally, a decade and a half after the first tentative steps, everybody seems to agree that this is the year that mobile BI will really take off.

2012 Is the Year of Mobile BI

Here’s a taste of the mountain of research data that’s been generated about mobile BI in the last few months:

• Boris Evelson of Forrester says mobile BI will go mainstream this year. “One needs to make decisions when and where they need to be made. Not ‘when I get back to the office,’ which may be too late.” He also says that “professionals must start evaluating and prototyping mobile BI platforms and applications to make sure that all key business processes and relevant information are available to knowledge workers wherever they are.”
• According to Gartner, “by 2013, 33 percent of BI functionality will be consumed via handheld devices.”
• A survey by analyst Howard Dresner indicates that BI has already become the third most in-demand enterprise mobile application, behind only email and personal information management apps such as calendars, and 68 percent of those surveyed rated mobile BI as “critical” or “very important,” up from 52 percent a year earlier.
• A recent survey by Information Week showed that 25 percent of organizations are planning to implement some form of BI this year.
• Sixty-one percent of the participants in a TDWI survey said that they expect users to spend more time accessing BI from mobile devices in the next 12 months.
• Business Intelligence and mobile are the top two technology priorities for CIOs in 2012.

Barriers to deployment

Not every organization is moving forward with mobile BI. Here are the main concerns:

• Security and administration: Organizations are concerned about data getting outside the organization, and the administration overhead generated by managing BI on mobile devices. A mobile device management (MDM) platform (not to be confused with the other MDM) like Sybase Afaria is key.
• Expectations-setting: An easy interface doesn’t mean that the data users want is readily available. New opportunities mean new requirements. Having the right data foundations in the first place, with a robust, standard BI platform in place makes it easier to react fast to user expectations.
• Platform choices: This is perhaps the biggest factor delaying widespread deployment. Just like the operating system wars of last century (remember IBM OS/2?), there’s no one obvious platform to standardize on for rolling out mobile applications. There are three main strategies, all with pros and cons:
  • Native applications—mobile applications written directly for iOs or Android. The advantage is optimal ease-of-use and access to the capabilities of the native device. The disadvantage is the cost and complexity of supporting multiple platforms and different user interfaces.
  • HTML—accessing mobile BI through a Web browser. The advantage is that you don’t care what device is being used to access the data – at least in theory. In reality, the disadvantage is that browser-based interfaces are generally far behind what’s possible using the native features. There are high hopes that the proposed HTML5 standard will help – but it hasn’tt yet reached maturity.
  • Hybrid solution—mobile enterprise platforms such as Sybase Unwired Platform. You create applications once, and then generate different versions of them optimized for different mobile platforms, including HTML. It’s an insurance measure against the turbulent real-life world of changing mobile platforms, but there’s some upfront investment.

An example of today’s mobile BI solutions -  SAP BusinessObjects Mobile showing the integrated Google maps pioneered by the Innovation Center.

Of course, most of us just want all these options to be available as part of the standard business intelligence platform – and that’s getting closer…

Next Steps

Gartner predicts that “by 2013, 15% of BI deployments will combine BI, collaboration and social software into decision-making environments”. In other words, mobile BI will become part of an “orchestrated” experience that combines accessing data with acting on it, and we’re starting to see this in the form of mobile medical analytics for doctors or mobile beauty advisor applications.

Interestingly, one brand new area of opportunities is the integration of mobile with voice-controlled interfaces such as Apple’s Siri. Business Objects was WAY ahead of the curve with this one, with the project codenamed “Ariel”. It sadly didn’t take off, but anybody who saw it demoed will have fond memories…

Here’s a recording of a World Tour keynote presentation (it happens to be from Belgrade, Serbia, but I did similar presentations in several different regions). It covers how companies can build competitive advantage through customer intimacy, product leadership, category renewal, and operational excellence, using examples from SAP’s customers.

You can download the slides in either PowerPoint or pdf format.

In a previous post, I talked about the “illusory superiority” effect, and how it blinds people to the fact that, on average, it’s unlikely that they use data better than their competitors.

Guess what? It turns out that it applies to governance, risk, and compliance, too. Here are some figures from another Economist Intelligence Unit Survey, “Ascending the Maturity Curve, Effective Management of Enterprise Risk and Compliance”:

We can see that of those who haven’t experienced failures, only 1% believe that they are worse than average – and even among companies that have experienced failures, fully 87% believe that they are as least as good as their peers.  Unless the Economist has stumbled across a particularly great group of companies to study, it seems clear that most organizations are overestimating the quality of their GRC practices, and hence underestimating the real risks they are running…

There’s also data in the report that seems to indicate that the finance function is the mostly likely to be blindsided – as you can see in the chart below, they are far more likely to say that there was no significant risk or compliance failure in the past three years. Since this is not a group known for their exuberant optimism, it’s likely that they simply didn’t know about the risks run by the other teams…

In conclusion, if you’re in the finance function, and responsible for your GRC practices, it’s likely that you should be investing more than you are today. For more information, check out SAP’s GRC products, and Norman Mark’s blog on Governance, Risk Management, and Internal Audit.

Here’s a video from this years SAPPHIRE NOW in Madrid, featuring Mimi Speir, Steve Lucas, and Andrew Murray giving an overview of SAP BusinessObjects mobile directions:

Highlights include:

• New SAP BusinessObjects experience mobile application, based on the Exploration Views functionality from the BusinessObjects innovation center, with demo data from Experience.SAP.com
• Easily take a mobile analysis and create a StreamWork activity for collaborative decision-making
• Easily “mobilizing” your existing BusinessObjects reports
• Support for each level of the “mobile needs hierarchy”, including fully customized mobile applications

• Demonstration of integration with RightHemisphere, a recent SAP acquisition that allows companies to synchronize visual and business data, combining a camera and schematic view:

Overlaying colors by temperature from data in the ERP system:

Finding a required part replacement using geolocation data:

Sybase (“an SAP Company”) recently published an analytics guide called “Intelligence for Everyone”.

The first section called “The Big Lie about Big Data” includes the following:

Why “big lie?” Because, as the article points with lots of historical examples, there’s always been a “crisis” in data storage, but as data volumes have risen technology has always evolved to deal with it, and that’s as true today as it has been in the past:

• 1956 Transaction data volumes overloaded current memory systems, leading to IBM’s creation of the first hard drive (costing $10,000 per Mb)
• 1970 Alvin Toffler’s book Future Shock popularizes the phrase “information overload”
• 1986 Technology critic Theodore Roszak:  “An excess of information may actually crowd out ideas, leaving the mind… distracted by sterile, disconnected facts, lost among shapeless heaps of data.”
• 1990 An IEEE conference features a session “Crisis in Mass Storage.”
• 1995 A Montreal data mining conference talks about the “data firehose phenomenon” swamping users

Interestingly enough, the guide manages to talk a lot about Big Data without mentioning what many people associate the term with: open source technologies such as Hadoop/Map Reduce. This is all the stranger because the latest version of Sybase IQ 15.4 includes a native MapReduce API and Hadoop integration, getting closer to the ideal architectures of the future that take the best of both worlds.

The guide also slides over the advantages of in-memory storage such as SAP HANA, noting just that “64-bit systems with their larger RAM space make this technology more attractive, if more expensive”

For more on SAP HANA and Sybase IQ, here’s analyst group Ovum’s take: “SAP’s HANA and Sybase IQ are separate but complementary“

The guide concludes that:

“Big Data is not to be feared. It’s to be exploited. The analytics industry today has no excuses when it comes to working with Big Data. It has no excuses when it comes to scaling their analytics data warehouse to include thousands of users. It has no excuses when it comes to applying analytics to variable data types from every imaginable source, including, for example, the vast unstructured information from social media sites.”

I was honored to speak at this years UK & Ireland SAP User Group Conference held in Birmingham, UK. The first main day saw great keynotes from the new SAP UK Managing Director, Steve Winter; Analyst Ray Wang; SAP’s CIO, Oliver Bussmann; and Olympic Sprinter Steve Cram. You can read a full review by Christoph Ziedler on SAP.info, and see the various videos on YouTube starting with the introduction by Alan Bowling, Chairman of UKISUG.

Here’s a selection of photos I took during the sessions:

And there are many, many more photos on the UKISUG Flickr Stream.

I gave the keynote on the second main day. Here’s the video taken by the organizers, including the slides:

You can download my slides in pdf format or in the original PowerPoint format.