I gave a presentation in Finland earlier this year as part of the Nordic “Butterfly” tour, talking about the future of Business Intelligence:

Ever since the first abacus, information technology has been an essential part of delivering timely information, staying accountable to stakeholders, reducing inefficiencies, and flexibility when faced with fast-changing environments. But for the first time in history, consumer technology interfaces have been outpacing what’s available to the average corporate knowledge worker.

How can we combine the best of enterprise technology and Web 2.0 to build greater visibility, transparency, and accountability into the way organizations work? Business intelligence technology needs to meet the demands of tomorrow’s “digital natives”; integrate seamlessly with cloud data and platforms; align people, conversations, and data with business strategy; and make the most of the infrastructures we have today:

• Simple: the right interfaces for the right people at the right time
• Seamless: tightly integrated with data sources, applications, and business processes
• Social: allow people to collaborate around analyzing information and making decisions
• Strategic: closing the loop between strategy to execution

The feedback from the audience was very positive, and so we’ve taken the 45-minute presentation and posted it to YouTube as a series of short, single-topic sections (see below). The presentation is available for download as an Adobe PDF document, and as the original PowerPoint presentation file.

The conference also included a more detailed BI presentation (not recorded) that focused on more leading-edge future BI topics such as social network analysis and augmented corporate reality. It is also available for download as an Adobe pdf file, and as a PowerPoint presentation file

Take a look, and if you find it interesting, please share with others in your organization! (and if you are interested in a tailored BI vision presentation for your company or conference, please contact me at telliott@timoelliott.com)

[Update: There’s now a nice convenient viewer for the various videos available:]

Part 1 Introduction (3:12 min)

Summary:

• High-level BI trends
• Brief summary of BusinessObjects porfolio

Part 2  Simple (9:05 min)

Summary:

• Taking BI to the next level: Simple
• Roadblocks to success
• Taking cues from the consumer world
• BI interfaces that you don’t need training to use
• Japanese picnics

Part 3 Simple Continued (4:23 min)

Summary:

• Adapting interfaces to end users
• Other interfaces, including mobile devices
• Going faster

Part 4 Seamless (9:33 min)

Summary:

• Taking BI to the next level: Seamless
• The importance of data
• Bridging the gap between central and personal data
• Text analytics
• BI OnDemand
• Embedded BI
• “Automagical” Text to Query

Part 5: Social (5:07 mins)

Summary:

• Taking BI to the next level: Social
• Collaboration is important
• Spitfire Marine example
• StreamWork demonstration

Part 6: Strategic (9:26 min)

Summary:

• Taking BI to the next level: Strategic
• Budgeting and finance
• Financial vs. other Risk
• Sustainability performance management
• Business applications of the future
• Conclusion

Ajay Ohri of DecisionStats.com has a selection of interviews with people in the BI/analytics space, including James Taylor and John Fox, the creator of R Commander.

Here’s an interview he did with me last week covering trends in predictive analytics, cloud computing, social network analysis, etc.

Timo- I studied economics with statistics in the UK, but I had always been a closet geek and had dabbled with computers ever since I was a kid, starting with Z80 assembler code. I started my career doing low-level computer consulting in Hong Kong, and worked on a series of basic business intelligence projects at Shell in New Zealand, cobbling together a solution based on a mainframe HR system, floppy-disk transfers, and Lotus 1-2-3 macros. When I returned to Europe, I stumbled across a small French startup that provided exactly the “decision support systems” that I had been looking for, and enthusiastically joined the company.

Over the last eighteen years, I’ve worked with hundreds of companies around the world on their BI strategy and my job today is to help evangelize what works and what doesn’t, to help organizations avoid the mistakes that others have made.

When it comes to BI initiatives, I see the results of one fundamental problem almost on a daily basis: 75% of project success depends on people, process, organization, culture, and leadership, but we typically spend 92% of our time on data and technology.

BI is NOT about technology – it’s about helping people do their jobs. So when it comes to education, we need to teach our technologists more about people, not science!

Ajay- You were the 8th employee of SAP Business Objects. What are the key turning points or transition stages in the BI industry that you remember seeing in the past 18 years, and how has SAP Business objects responded to them.

Timo- Executive information systems and multidimensional databases have been around since at least the 1970s, but modern business intelligence dates from the early 1990s, driven by the widespread use of relational databases, graphical user interfaces, and the invention of the “semantic layer”, pioneered by BusinessObjects, that separated business terms from technical logic. For the first time, non-expert business people had self-service access to data.

This was followed by a period of rapid expansion, as leading vendors combined reporting, multidimensional, and dashboard approaches into fully-fledged suites. During this period, BusinessObjects acquired a series of related technology companies to complete the existing offer (such as the leader in operational reporting, Crystal Reports) and extend into enterprise information management and financial performance management.

Finally, the theme of the last few years has clearly been consolidation – according to Gartner, the top four “megavendors” (SAP, IBM, Microsoft, and Oracle) now make up almost two-thirds of the market, and accounted for fully 83% of the growth since last year. Perhaps as a result, user deployments are accelerating, with usage growth rates doubling last year.

Ajay- How do you think Business Intelligence would be affected by the following

a) Predictive Analytics.

Timo- Predictive analytics has been the “next big thing in BI” for at least a decade. It has been extremely important in some key areas, such as fraud detection, but the dream of “no longer managing by looking out of the rear-view mirror” has proved hard to achieve, notably because business conditions are forever changing.

We offer predictive analytics with our Predictive Workbench product – but I think the real opportunity for this technology in the future is “power analytics”, rather than “prediction”. For example, helping business people automatically cluster similar values, spot outliers, determine causal factors, and detect trend inflection points, using the data that they already have access to with traditional BI.

b) Cloud Computing.

Timo- In terms of architecture, it’s clearly not about on-demand OR on-premise: it’s about having a flexible approach that combines both approaches. You can compare information to money: today, we tend to keep our money in the bank rather than under our own mattress, because it’s safer, more convenient, and more cost-efficient. At the same time, there are situations where the convenience of cash is still essential.

Companies should be able to choose a BI strategy, and decide how to deploy it later. This is what we offer with our BI on-demand solutions, which use the same technology as on-premise. You can start to build on-premise and move it to on-demand, or vice-versa, or have a mix of both.

In terms of data, “cloud intelligence” is still a work in progress. As with modern financial instruments, we can expect to see the growth of new information services, such as our “information on-demand” product that provide data feeds from Reuters, Thompson Financial, and other providers to augment internal information systems. Looking further into the future, we can imagine new information marketplaces that would pay us “interest” to store our data in the cloud, where it can be adapted, aggregated and sold to others.

c) Social Media.

Timo- Conversations and collaboration are an essential part of effective business intelligence. We often talk about the notion of a “single view of the truth” in this industry, but that’s like saying we can have “a single view of politics” – while it’s vital to try to give everybody access to the same data, there will always be plenty of room for interpretation and discussion. BI platforms need to support this collaborative decision-making.

In particular, there are many, many studies that show up our all-too-human limitations when it comes to analyzing data. For example, did you know that children with bigger feet have better handwriting?

It’s absolutely true — because the children are older! Mixing up correlation and causality is a common issue in business intelligence, and one answer to the problem is to add more people: the more reviewers there are of the decision-making process, the better the decisions will be.

Analysis is also critical to the development of social media, such as analyzing sentiment trends in Twitter — a functionality we offer with SAP CRM — or tracking social communities. For example, Jive, the leader in Enterprise 2.0 platforms, offers our BI products as part of their solution, to help their customers analyze and optimize use of the system. Administrators can track if usage is trailing off in a particular department, for example.

d) Social Network Analysis.

Timo- Over the last twenty years, partly as a result of extensive automation of operational tasks with systems such as SAP, there’s has been a huge shift from “routine” to “non-routine” work. Today, fully 90% of business users say that their work involves decision making, problem solving, and the creation of new analysis and insight.

To help support this new creativity, organizations are becoming more porous as we work closer with our ecosystem of customers, partners, and suppliers, and we work in ever-more matrixed environments and cross-functional teams.

We’ve developed a Social Network Analyzer prototype that combines BI and social networking to create a “single view of relationships”. It can gather information from multiple different systems, such as HR, CRM, email distribution lists, project teams, Twitter, etc., to create a multi-layered view of how people are connected, across and beyond the enterprise. For more information, see the SAP Web 2.0 blog post, and you can try it yourself on our ondemand.com web site.

Ajay- What is the area that SAP BusinessObjects is very good at (strength). What are the key areas that you are currently seeking to improve ( opportunities)

Timo- Companies evaluating BI solutions should look at four things: product functionality for their users’ needs, fit with the overall IT architecture, the vendor’s reputation and ecosystem, and (of course) price. SAP BusinessObjects is the clear leader in the BI industry, and I’d say that SAP BusinessObjects has the best overall solution if you’re a large organization (or looking to become one) with a variety of user needs, multiple data sources, and a heterogeneous IT infrastructure.

In terms of opportunities, we have high expectations for new interfaces for casual users, and in-memory processing, which we have combined in our SAP BusinessObjects Explorer product. Initial customer feedback has been excellent, with quotes such as “finding information is as easy as using the internet” and “if you can use a computer, you can use Explorer”.

In terms of future directions, we’re taking a very transparent, Web 2.0 approach. The SAP BusinessObjects innovation center is modeled on Google Labs and we share our prototypes (including the Social Network Analyzer mentioned above) with anybody who’s interested, and let our customers give us early feedback on what directions we should go.

Ajay- What does Timo Elliott do for work life balance when not writing, talking, and evangelizing about Business Intelligence?

Timo- I’m a keen amateur photographer – seewww.timoelliott.com/personal for more!

Highly Relevant

Memory Spot. This miniature wireless data chip, 2mm to 4mm square, can be stuck on, or embedded in, any object. Prototypes of the chips can hold as much as 4Mbit and future versions are expected to store several megabytes. Relevance to BI: Seems curiously undersold in the Computerworld article (movie trailers on posters?!). RFID on steroids: when combined with cheap sensors, this would potentially allow any object to store vast amounts of information about itself and its interaction with other devices.

Apollo (honorable mention). This cross-operating system application runtime allows Web developers to use their existing skills to build and deploy rich Internet applications on the desktop, so users can engage with Web applications even if there is no Internet connection. Relevance to BI: BI is a great example of environment that needs to seamlessly switch between thin-client online access (accessing an alert) and rich local functionality (drilling down into causes) — expect to see Apollo or similar technologies take an increasing role in BI interfaces.

Data Governance

One of the winners and three of the “honorable mentions” are directly relevant to BI and data security. The phrase “Information is Power” is truer than ever, organizations are becoming increasingly porous, and it’s no longer enough to put in place simple restrictions. Basic access security is giving way to data governance, including the management of the complex real-life relationships between information and users. Healthcare is a great example — there are many, many different people that require some sort of access, there has to be privacy for individuals, but the same data is essential for clinical analysis — how can you ensure that researchers can never get enough data to compromise an individual’s privacy?.

Data governance will spawn an entire new industry. Tighter controls over data storage, archiving, and transmission, and managing identities and relationships will all be part of it. (By the way, just in case anybody is still fooled, retention policies are really “deletion policies”. Especially with new text analytic technologies, any incautious emails and documents can come back to haunt you. Don’t write anything, ever, that you wouldn’t like to see published on the web.)

An Identity Passport. This combination of services and software helps consumers manage their online identities and ensure security of online transactions, with a goal of creating a universally accepted identity system for consumers across all Web sites, similar to a passport. 

DataDefender. This information leak-stoppage appliance uses a digital fingerprinting algorithm to monitor information traffic and block confidential information from leaving the network. The tool combines insider threat management technology, including real-time breach monitoring and remediation capabilities.

Security Suite. BitArmor protects, tracks and manages data throughout the company at wire speed so users won’t notice any delay. The software protects data on laptops, desktops and application servers, and can seamlessly encrypt, classify, apply retention policies to, suspend access to and destroy any data stored anywhere in the organization. 

ActiveSentry .  This intelligent desktop security software prevents employees from accidentally or maliciously distributing private data to the outside world. ActiveSentry monitors a broad array of distribution methods, including e-mail, instant messaging, blogs, file transfer, printing and removable storage devices, such as memory sticks or CDs. Uses ContextIQ, a context-based engine that automatically understands a user’s intent or meaning and triggers real-time alerts.

Of Interest

Smart Talker. This intelligent command engine bridges natural language and computer language, allowing machines to “understand” the actual meaning embedded in a sentence. Relevance to BI: If it works, very relevant — but decades of previous failed attempts means that it should be taken with a pinch fistful of salt (will we ever interact directly with computers? will they be like Marvin or Eddie the shipboard computer?).

Web Surfing with Eye Gaze. EyePoint makes it possible for eye-gaze to be used as a viable alternative to a mouse. Relevance to BI: Part of the Matrix / Minority Report interface future?

Slice-and-Dice Dispersed Storage. Cleversafe slices, scrambles, compresses and disperses data over the Internet to disparate nodes (servers) on a grid. Relevance to BI: we’ll always be in the market for better, more secure storage of data

Power-Packed Memory. A memory compression technique that more than doubles the amount of usable memory in embedded systems such as cell phones without any changes to hardware, without any changes to applications, and with negligible performance and power consumption. Relevance to BI: today’s users expect data “ATAWAD” — any time, any where, any device. Anything that boosts device memory can only help speed mobile BI deployments.

Who Cares?

Wearable Gadgetry. Users can see schedules, phone numbers, addresses and recent e-mail messages without having to start up their laptops. Relevance to BI: Drill on alerts embedded in your jacket sleeve? I think not.

The Everywhere OS. Ghost moves the operating system onto the Web, providing users with a Ghost virtual computer — a free PC environment accessible from any browser.  Relevance to BI: ghostly, at best.

Observation Grid. Globus Medicus is a robust and user-proven method for sharing 3-D medical images on a grid. Relevance to BI: better network speeds? ho-hum.

SC 5832 (honorable mention). This complete cluster node on a chip. A SiCortex cluster node with DDR-2 memory consumes less than 20 watts of power, an order of magnitude less than the 250 watts used in a conventional cluster node, dramatically improving communication latency and bandwidth. Relevance to BI: so it’s faster, smaller, and greener — but what else do we expect?