Why did it take so long to discover the source of the deadly outbreak of E.coli poisoning in Germany? Since the start of the outbreak, 35 people have died, over 100 will need kidney transplants or life-long dialysis, more than 3,000 people are ill, and falsely-accused Spanish cucumber producers have lost millions of Euros.

Researchers initially relied on the most obvious source of data: the tests carried out on suspect food. Unfortunately, the thousands of tests on farms throughout the country came up negative, even in the organic farm in Lower Saxony that now seems to be at the cause of the problem. They also carried out two surveys. The first showed that people who consumed raw tomatoes, cucumbers, and lettuce were more often sick than the others, and another case study showed a strong association between the consumption of foods from the salad bar and E. coli infection – but this wasn’t enough to narrow down the origin of the outbreak.

It was only when a detailed cohort study was carried out, including one group of nineteen Swedes that had all eaten in the same restaurant, that the data showed that those who had eaten the sprouts were nine times as likely to have gotten sick.

According to Daryll E. Ray & Harwood D. Schaffer:

“To ascertain the consumption of raw fruit and vegetables by patients and controls more objectively and less dependently on memory, RKI used the following approach in the ‘recipe-based restaurant cohort study:’ Five groups (travel groups, clubs, etc.) that comprised a total of 112 participants and included 19 individuals who acquired EHEC infection were questioned regarding the foods they consumed after eating in a common restaurant. Additionally, the menus ordered by the participants were identified by means of order lists and meal receipts. The restaurant kitchen was questioned in detail regarding the preparation and the type and quantity of ingredients in each menu ordered by any of the study participants. Furthermore, available photographs taken by travel group members were analyzed to confirm which food items, including toppings, were seen on the plates. The data thus gathered was analyzed in a cohort approach that permits the retrospective estimation of the relative risk of infection for the restaurant customers. Results of this analysis showed that customers who ate sprouts had an 8.6-fold increased risk [of] illness compared to those who did not. This study also revealed that 100% of those who contracted the illness had eaten sprouts.”

The decision process was made all the more difficult because it appears some records were held on paper rather being completely computerized, and health authorities were sometimes communicating with hospitals and each other via letters in the post rather than electronically, and were having trouble tracking who had become ill.

An overly-manual and confused decision-making process hindered the discovery of the “sproutbreak” that lead to so much suffering and hardship. But at least some good has come out of it: a better process, and a more detailed questionnaires will now be a standard part of outbreak investigation in the future.

All organizations need to be able to document and improve their decision-making processes, even if (thankfully) it’s rarely a case of life or death. Technologies like SAP Streamwork are starting to allow companies to apply standard templates to frequently-occurring decisions, and collaborate to come to the best conclusions, using an on-demand platform.

Could you improve decision-making in your organization by optimizing decision collaboration?

Other Links

• http://scienceblogs.com/aetiology/2011/06/german_officials_declare_e_col.php
• http://scienceblogs.com/thepumphandle/2011/06/culprits_in_germanys_foodborne.php
• http://www.rki.de/EN/Home/homepage__node.html

Evernote is a great Web 2.0 application that is focused on “helping the world remember everything”. It lets you grab information on the fly, such as notes, web pages links, photos, etc. from a variety of different devices (PC, Blackberry, etc.) and let you store them in your Evernote account. Everything you upload is automatically processed, indexed, and made searchable (for example, if you take a picture of some text, Evernote automatically uses text recognition and makes the text searchable). And you can add tags or organize notes into different notebooks.

The Evernote API allows other applications to integrate with the Evernote platform. This was used by the SAP StreamWork team to allow you to bring information from your Evernote account into a StreamWork activity

Now Evernote has launched the Evernote “Trunk” of applications that extend and connect to the “Evernote memory platform”. SAP Streamwork is the first application featured on the new site.

Evernote have put together a blog posting on how to use the two applications together, and there’s a StreamWork tutorial video available:

Press coverage:

• Evernote Launches Trunk Productivity App Platform, Fritz Nelson, InformationWeek
• Evernote Trunk To Add Hundreds of Apps and Features, Robert Strohmeyer, PC World
• Evernote Launches ‘The Trunk’ to Showcase Integrations Built on the Evernote Platform, TMCNet
• Evernote Turns Itself into a Platform with “Trunk”, Liz Gannes, GigaOm
• Evernote, the Startup that Augments your Memory, Launches an App Store, Kim-Mai Cutler, VentureBeat

It’s now official: SAP has released its brand-new Web 2.0 product called StreamWork. The project was initially called “Constellation” within SAP, and was first exposed to beta customers on the web site 12sprints.com, as covered in earlier postings on this site.

Why the name? It’s a variant on “workstream”, which according to Wikipedia is:

“A flow of output, the activities and transactions, that a worker produces as they go about their daily work activities. Workstreams are flows of largely unstructured data that workstreaming technologies seek to capture, document and repackage in more intelligent ways benefiting individual workers, managers and corporations.”

And the article goes on to say:

“…tapping into and mining these workstreams presents tremendous opportunities to companies in terms of collaboration, agility and collective intelligence.”

Other research seems to back this up. According to a study by Frost & Sullivan, 36% of company performance is determined by organizations’ “collaborative index”:

“This is more than twice the impact of a company’s strategic orientation (16%) and more than five times the impact of market and technological turbulence influences (7%). This is a key finding because it empirically demonstrates that increased high-quality collaboration can improve business performance.“

The Power of Collaborative Decisions

Every person in every organization makes many decisions every day. Many of these are so small that we don’t even recognize them as decisions. Every time a sales person calls a customer, she is “deciding” to prioritizing that activity over everything else she could be doing. Of course, a sub-optimal decision may not make much difference. But over time, and across a large organization, these small decisions pile up and have a huge influence to corporate performance.

Of course, computer systems have been promising Improved business decision-making since at least the 1950s, by providing more information about company operations. And they have largely delivered, enabling corporations of breath-taking complexity. But you can give everybody the same facts, and still end up with completely different views about what the data means, and what should be done about it (just look at any group of rival politicians!).

Decision-making is a core business function of every organization, and has been extensively studied by scientists and management theorists. But despite all the advances in theory, real-life decision-making is still dominated by people, personalities, and endless emails and meetings.

Decisions still tend to be made in messy, non-repeatable, “are-we-really-sure-about-this?” ways, relying heavily on “gut feel”. People often spend more time and effort making decisions as they do on actually trying to execute them, and reviewing / reversing decisions that have already been made (every new politician and executive feels honor-bound to reverse the decisions of their predecessors).

Collaboration or “Enterprise 2.0” platforms, including Jive and Cubetree and Google Wave have helped, by letting employees work together on projects, but they typically don’t directly support goal-oriented decision-making.

Introducing SAP StreamWork

StreamWork helps you bring together:

• All the right people needed to make a good decision (executives, influencers, experts), across different corporate functions and geographies
• All the information relevant to the decision, from inside or outside the organization, both qualitative and quantitative, objective and subjective (and reformat it, if necessary). Integration with Evernote and Scribd makes it easy to upload and share documents.
• All the right methods that should be brought to bear in order to consider all the aspects of the decision (cost/benefit analysis, SWOT analysis, Pro/Con charts, responsibility matrices, etc.)

See this link for a summary of StreamWork features and view the StreamWork YouTube Channel for an extensive set of how-to videos.

By putting all this in one environment, and letting people collaborate and comment and add data and add documents, and explain their reasoning, organizations get:

• More clarity about why decisions are being made
• More engagement from employees, who can see a direct link between their suggestions and the final result
• More commitment to decisions (research shows that we care more about fair process than we do with final decisions. If we feel our voice has been heard, we’re far more likely to comply with the final choice, even if we didn’t agree with it)
• Better results. Measurement and tracking of the decision-making process, allowing you to optimize the process over time (faster decision cycles, better outcomes)

On-Demand, Extensible Architecture

StreamWork uses an on-demand architecture, so you can be productive immediately without any software installs, and you can easily invite people from inside or outside the organization without having to worry about access problems. And it provides an open REST API, making it easy to extend StreamWork functionality and integrate with other systems.

Here’s a look at some of the add-ons that have already been built, including integration with InfoView, Text-to-query, Android, YouTube, and others.

Here’s a great example of the integration possibilities from OffiSync:

And SAP is busy integrating other prototypes such as Gravity, covered in an earlier post, with StreamWork.

Pricing

The basic edition is free, with up to five activities, 250Mb of storage, and the unlimited ability to collaborate in others’ activities. The Professional Edition costs $9/month for up to 100 activities, 5Gb of storage, and more control over user security. An Enterprise Edition is in the works, with more details to be announced later this year.

Sign up Now!

Signing up for StreamWork is easy and free — click here.

Other Coverage and Links

• Alex Williams, ReadWriteWeb: Does StreamWork Give a Picture of SAP’s Future?
• Bob Thompson, Customer Think: Will StreamWork get SAP out of its Innovation Funk?
• Chris Kanaracus, IDG News: SAP’s ‘Virtual War Room’ Tool Gets a Name: StreamWork
• Jon Brodkin, Network World: SAP Targets Online Collaboration Market with StreamWork
• Larry Barrett, Datamation: SAP Debuts Cloud-Based Collaboration Apps
• Xavier Lanier, GottaBeMobile.com: Evernote’s Incorporated in SAP Collaboration Tool
• B-Eye-Network: Formerly Known as 12sprints, SAP StreamWork is now Generally Available
• Rich Hoeg: 12Sprints Tutorial

SAP’s decision-focused collaboration project, 12sprints, is now in “open beta”, so that anybody can sign up. Here’s the blurb from the web site explaining what it is:

Bring order to chaos and transform teamwork into results quickly. Collaborative decision-making brings together:

• People – Get everyone on the same page
• Information – Share documents and data all in plain view
• Methods – Provide structure with business tools for brainstorming, strategizing, and decision-making

And it’s built for speed – use for free and be up and running in minutes!  Learn more

For an introduction to a typical activity structure, and a real-life example, please visit this post on TimoElliott.com

[post updated to reflect new name, StreamWork]. SAP’s decision-focused collaboration project, 12sprints, is now in “open beta”, so that anybody can sign up. Here’s the blurb from the web site explaining what it is:

Bring order to chaos and transform teamwork into results quickly. Collaborative decision-making brings together:

• People – Get everyone on the same page
• Information – Share documents and data all in plain view
• Methods – Provide structure with business tools for brainstorming, strategizing, and decision-making

And it’s built for speed – use for free and be up and running in minutes!  Learn more

This post gives an introduction to what you can do with the technology, and points you to some useful links. First, here’s a video that explains some of the basics, and you can find a full set of Tutorial Videos on the SteamWork YouTube Channel.

When you log in, you’ll see a screen like this one:

Once you’ve signed up you can start to create activities. In order to show you a glimpse of some of the things you can do, lets look at a couple of examples.

A “First Introduction to StreamWork” Activity

Here’s an example Activity I put together to illustrate the concepts and tools available in StreamWork. Each “activity” is broken down into sections, or “activity tools” chosen from a large catalog of possibilities. In this example, I’ve pulled in a selection of these tools to explain the overall layout of a typical decision (in this case, I chose to discuss a high-level comparison of StreamWork and other collaborative environments).

Here’s an overview of the activity, and then we’ll look at each section in turn:

The first block in the example is an introduction to the activity, to explain to new participants what the Activity is about, where to get more information, etc. Participants can make comments on any section, and add links to other resources to back up their arguments. Note also the feedback tab on the right-hand side – this opens a full forum designed to streamline user feedback about the prototype, powered by UserVoice.

StreamWorkis focused on decision-making, so let’s start by explaining the decision we’d like to make:

Let’s add an example of one of the most basic decision-making tools – a comparison table. Note that we can change from a “list view” to a “single item” view in order to see all the information without scrolling.

Here’s another simple decision tool – a pro/con table. Participants can add their own pro/con comments. I can see the information as a simple table, and mouse-over to see the details:

Or I can expand the table to see the full set of information:

You can group several related activities into a single high-level section:

Finally, here’s another simple tool, asking people to give their reactions to the decision and the process (positive/neutral/negative):

Throughout this process, you can make comments, upload documents, add invite/manage participants using the menu at the top of the screen. There’s also the ability to add and track action items for basic “decision workflow”

Here are some of the other tools you can currently add – the goal is to extend these over time.

A “Real” StreamWork Example

I wanted to get a feel for what it would be like to use StreamWork in a real situation, so I applied it to a life decision of my own: whether or not I should vaccinate my daughter against the H1N1 flu virus (the “swine flu”). I was pretty sure it was the right thing to do, but I knew others disagreed, so I wanted to understand their point of view, and see if that would sway my decision. Here’s the full activity, as an image:

Conclusion

I didn’t change my mind about vaccinating my daughter – but the process certainly opened my eyes to aspects of the decision-making process that I had not taken into account, and I ended up with a much better understanding of why others might disagree. I believe that this aspect – making sure that all relevant angles are being taken account of when making a decision – will prove extremely useful in real-life implementations.

Other links

• Chris Kanaracus, SAP’s Enterprise Collaboration Tool Entering Public Beta
• Clint Boulton, eWeek, SAP Offers 12Sprints As Enterprise Alternative to Google Wave

You can now sign up to be a beta participant of SAP’s 12sprints project, “a collaborative environment for people to make better decisions based on data” or a “people-connecting, data-sharing, decision-making tool that actually sets work in motion.”

Early versions of the prototype were glimpsed during demonstrations by Léo Apotheker and Ian Kimbell at SAP SAPPHIRE in Berlin last year, and by Marge Breya at SAP TechEd in Vienna, and the project is now letting people sign up for pre-beta access to the prototype.

Beta users will get access to a “virtual war room” with various types of decision-making tools available. According to the www.12sprints.com site:

“It’s not just a place where things get discussed. It’s where things get done. Invite the right people. Bring in the pertinent data. And choose the most informed course of action with the help of pre-defined, interactive decision-making tools. It’s all built in. Everything you need to get everyone on the same page — finally under one roof.”

Marge Breya recently repeated her SAP Tech Ed demo for Information Week’s Fritz Nelson, with a scenario based on people collaborating on go-to-market strategy after a new company has been acquired:

“…[it’s] about a purpose-driven experience, and the user gets to design it. So I can set up my own purpose whenever I want, invite the people I want, and get the exact data I want and expertise at my fingertips.”

Marge is invited to review the current decision goal, timeline, data etc.

Marge decides that she disagrees with the current plan, so enters a new negative opinion:

And uses another labs project called “Kona”, the next generation of on-demand business intelligence, to get the data she needs:

Here’s the full video:

And here’s Fritz’s commentary:

“We began with 12 Sprints, which I can best describe as a collaborative workspace, with a combination of project management and data sharing. You can pull in rich data feeds and share knowledge and make decisions, all in real time. In some ways, it resembles the modern Wiki. Where we explored other tools that help find and analyze data, 12 Sprints is where you would bring the most pertinent information back for team decision making.”

“Both 12 Sprints and Kona are cloud-based applications, run by SAP. Neither are available today, but both are expected to enter beta testing in November, with full release set for the first quarter (Kona) and first half (12 Sprints) of 2010.”

Business intelligence used to be called “decision support systems”, but the tools available have typically focused on gathering information, not the real-world collaboration required to turn that data into actual decisions and actions.

But that’s changing rapidly. According to Gartner:

“2009, Collaborative Decision Making will emerge as a new product category that combines social software with BI platform capabilities”

If you’re interested in finding out more, you can get news by following the 12sprints team on Twitter or by signing up to be one of the first to get exclusive access to the beta.

So each time I have my coffee and croissant, some of the 7 million or so visitors to the tower each year come out of the metro and consult this map of the 7th Arrondissement to try to help them figure out which way to go.

Here’s a close up – the Eiffel Tower is at the top left of the map below:

Let’s do a simple test of your information-processing skills. You’re a tourist, and you want to visit the Eiffel Tower. Should you turn left or right?

I’ll give you the answer, and some commentary about the implications of this on corporate decision-making, after the break: a bunch of photos of tourists doing the real-live test (it took only ten minutes to take this series, on a slow day)

The answer is: you turn to your right (personally, I’d recommend walking through the Champs de Mars, via the green trees on the right-hand side of the top picture).

Because the map is “upside down” (you are facing south as you read it), this is deeply unintuitive for most people, and they spend several minutes puzzling over it, sometimes eventually wandering off in the wrong direction, only to reappear a few minutes later with sheepish looks on their faces.

So how does all this relate to real-life decision making?

Missing the big picture. You see a map, so you use the map to try to figure out where to go. But look at the top picture again, at the signs on the left-hand side. See the one that points explicitly to the Eiffel Tower? You already did? Congratulations! – almost none of the tourists do.

In business, too, one of the big issues with analyzing data is starting in the wrong place, and getting so concentrated on a particular type of analysis that you miss that other techniques might be more important. For example, a company might put a lot of emphasis on financial analysis, but forget to do any customer surveys.

For example, an enterprise software companies might try to to ascertain product “worth” by calculating revenue by product. But since the products are not sold independently, but are instead bundled into large deals with lots of other products, the calculations are (worse than) useless.

More concretely: if, say, Xcelsius is allocated $10,000 of revenue from a million-dollar deal, but I would have lost the deal to a competitor without it, the product is “worth” way more than $10K, and I should plan my future investments accordingly. In this case, the “softer” customer survey data of why they purchased would be more reliable and valuable.

More information needed. Your first reaction to the test may have been “I don’t have enough information”.

But the placement of the red dot is very clear. You can only be at the corner of avenue Bosquet and avenue de la Motte-Piquet, facing out into the center of the Place de L’Ecole Militaire. In theory, the average person with enough money to travel to Paris should be more than capable of visualizing themselves on the map and making the right choice within a few seconds.

But this is not what happens. The average tourist reaches up and puts their finger on the big red dot and spends at least a minute looking around wildly for some other guidance. I’m guessing this is because (a) it takes effort to rotate a map in your head (and they’re on vacation) and (b) they are looking for a second opinion.

This is true in business, too.

First, you shouldn’t make people work too hard to understand the data. For example, you should never show an audience slides that just show charts, with no conclusions.

Instead, prove to them that you didn’t just stick the data on the slide without even considering it (sadly, all too common, at least in marketing). Put the key points you think the data shows, next to the numbers, and then the audience can use their thinking time and effort to agree or disagree with you, and consider the implications, rather than pointlessly redoing your analysis.

And second, like the tourists, I want more than one data set. I’m much too cynical about data quality, so you should attempt to gather some other form of information (a survey, say) that comes to the same conclusion.

Limited collaboration. The tourists often talk among themselves about the decision (I saw one poor preteen kid that had to explain it to his parents five times in a row before they understood) – but they rarely actually ask somebody outside their group (such as anybody nearby not dressed as a tourist).

The same happens in business. The small team has been tasked with the analysis. They feel that it’s their job to go and get numbers from people, but they rarely discuss the decisions or data outside the small team, even if there are other non-executives that may actually have strong insights into the correct answer.

For example, a classic marketing analysis gaff is to do analysis and and start executing a plan without actually asking the sales people their opinion. They have their own biases, but they will often point out that some aspect of the plan is perfectly stupid.

Making it overly-complex. Just in case there are some super-geeks out there: yes, you can work out the right way to turn by assuming, correctly, that it’s morning (the coffee and croissant) and that the light is coming from the East, so West is to the map-reader’s right. But let’s face it, if you managed to spot all that, I suspect you’d read the map right in the first place.

Presentation is important! One morning, I volunteered directions to several folks that had spent a long time looking at the map, only to find that they didn’t want help. The difference? I was dressed in shorts and a t-shirt and hadn’t bothered to shave before my morning run. To the tourists, I looked like a walking, talking data quality problem, and not to be trusted.

This is why technologies like Xcelsius, that present the data in a very attractive way, are so important. It shouldn’t matter, but it does. Even if you don’t need Xcelsius for the whole company, I strongly recommend you buy a single standalone copy for when you need to present to the board or executive team — it’s worth its weight in gold.

Fixing the Problem

It drove me nuts watching all these people. So I bought a two-euro indelible marker pen designed for CDs from a store opposite and drew some arrows on the map: “you are facing this way”, “your left”, “your right”, and “behind you”.

The results:

(1) It didn’t seem to help much. You still have to “rotate the map in your head”. A few people clearly attempted to follow the advice (e.g. craning to look upside down), but even then some of them went the wrong way.

(2) So many people put their fat fingers on the sign while they were trying to figure it out it that the arrow wore off in less than a day.

Interestingly, I was in London a few weeks ago, and I’d noticed that they had spent considerable time and effort on exactly this problem.

At the Legible London site, they explain what they’ve done to make it easy for tourists to find their way around. They’ve added clear direction arrows on the edge of the signs to major destinations, and extra information like walking times and distances.

And, in particular, they use “Heads-up” mapping:

Rather than having north at the top, on-street signage maps are ‘heads-up’, which means they’re orientated to face the same way as the user is facing. This helps people understand their immediate environment more easily.

Here’s an example from the site:

How does this relate to corporate decision-making?

The basic analysis is the same — YOU might understand that chart at a glance, but it’s very easy to overestimate the analytic skills of your audience, even if they’re highly educated!

Keep it simple and clear. As with the “heads-up” maps, this may take extra effort (London had to work out in advance where the maps were going to be installed and which direction they were going to face).

You have to not only spend time coming to conclusions from the data, but also spend time and effort to make sure that the analysis is clear to others!

And this is even more true in situations where you’re trying to give ad-hoc analysis tools to people. It’s almost impossible to imagine just how simple it has to be in order to be clear. Recommended best practice is to start with the simplest possible set up, and slowly, slowly introduce new features as people get comfortable.

As we’ve seen, it’s more than worth the extra effort. How many hours of confusion and frustration could the city of Paris save if they adapted the same types of maps? How much would it increase visitor satisfaction?

This report predicts a new style of decision support system — collaborative decision making (CDM) — will emerge in 2009 that combines social software with business intelligence (BI). This combination can dramatically improve the quality of decision making by directly linking the information contained in BI systems with collaborative input gleaned through the use of social software.

Read the full report here (and thanks to Nic Smith of Microsoft for the link).

A new “Decision Engine” called Hunch was launched today. How might this type of technology relate to collaborative decision-making in enterprises?

Hunch’s tagline is “Hunch helps you make decisions and gets smarter the more you use it.” From the web site:

What is Hunch? Hunch is a new way to help people make all kinds of decisions, such as:

• Where should I go on vacation?
• What’s the best US college for me?
• What kind of smartphone is right for me?
• Which museum should I visit in the Netherlands?
• What blog should I read?

Results are based on the collective knowledge of Hunch’s users. Hunch already has more than 2,500 possible topics, and Hunch users add new topics every day.

Hunch asks you 10 questions or less, some about what you need or want and some about who you are. Like a human expert, Hunch chooses questions intelligently and adapts them depending on how you answer.

After asking you questions, Hunch offers you a result. You can leave feedback on Hunch’s results and also explore other results based on the input of Hunch users.

You can train Hunch or correct a fact it got wrong. This is how Hunch learns and gets smarter. Topics get smarter as more people train them. So new topics may start out not so smart, but they’ll get smarter over time.

Users contribute to Hunch in various ways:

• Don’t like the questions that Hunch asked you? Submit a different question.
• Don’t see the result you wanted on Hunch? Propose a better result.
• Looking to make a decision that isn’t on Hunch? Add a new topic.

See the rest of the tour

It certainly seems like useful technology – and might be even more useful in a corporate context. How many times do different people need to make similar decisions, but end up doing it in completely different ways, because there’s no common context or methodology? How much could performance be improved if everybody made decisions as well as the best person (or better)?

Guided Analysis

The enterprise equivalent of this technology has been typically been called “guided analysis”: helping business users undertake analytic tasks by stepping them through a series of actions, and (without the web 2.0 angle) it’s been available in various guises in existing BI solution portfolios.

For example, the BusinessObjects Analytic Applications from a few years ago included ‘storylines” that helped analysts move from one analytic to another:

And the applications included workflow tools for predefined lists of analytic steps (for example, this was used by Somerfield supermarkets in the UK to ensure that each business analyst looked at the right analytics when reviewing which products to stock).

This technology was then incorporated into the BusinessObjects Encyclopedia part of the standard SAP BusinessObjects platform functionality. Administrators could set up Business Questions and suggest reports and measures that might be useful in answering the questions:

And set up “storylines” for the Guided Analysis tab of the Encyclopedia.

These storylines are then available to anybody using the portal.

Sadly, anecdotal feedback suggests that awareness and usage of this functionality has been fairly low, in part because of the maintenance requirements, but also because a lack of business skills within the IT organization, or because there was simply no agreed best practice to be recorded.

Looking forward, this type of functionality (along with workflow, discussion threads, rating, etc.) is becoming an essential part of an information platform layer designed to provide a consistent set of workflow and guidance across all information sources and activities (e.g. BI, planning and budgeting, collaboration around information management, etc.)

As the industry matures, we’re moving from BI efficiency (helping people access information quickly) to BI effectiveness (making sure that people are analyzing the right things in the right way) and effective guided analysis is an important part of this process.

Human nature means that it’s very hard to spend the time necessary to put together good best practice workflow. Allowing business people not only to collaborate around data, but also collaborate around processes for best practice decision-making will clearly be a big part of the future of “BI 2.0” and business user applications.

February 12th 2009 will mark the 200th anniversary of the birth of naturalist Charles Robert Darwin. He researched, popularized, and will forever be associated with what is probably the biggest idea ever: Evolution.

Despite the overwhelming evidence, there are still, sadly, many people who don’t believe in it. According to The Economist: "In the United States a Gallup poll conducted last year found that only 14% of people agreed with the proposition that “humans developed over millions of years”, up from 9% in 1982."

At one level, it’s not their fault. Evolution argues, after all, that we are all just meat-based bundles of algorithms designed to perpetual our genes.

It shouldn’t be any surprise that we are sometimes quite astoundingly bad at evaluating data and making decisions.

Here’s just a very short, incomplete, list of some of the things that we know we do badly:

• We’re far more open to data that confirms our existing beliefs
• We value things more just because we happen to already own them
• We value 300 cents more than $3
• We prefer to let others make decisions for us
• We prefer to punish others rather than make a gain
• Even exposure to random numbers can influence decisions

So, ironically, a refusal to accept the theory of evolution might actually be viewed as evidence for its existence. Certain types of belief and superstition appear to be (or to have been) more important for long-term survival than simple logic. Or maybe the observed problems are unfortunate side-effects of more important algorithms.

Technology Needs to Make up for Flawed Human Beings

All this has consequences on business intelligence. Ultimately, there’s no point in investing a fortune in providing the right information, at the right time, to the right person if they are going to brazenly ignore or misinterpret it.

Technology obviously can’t “fix people,” but should do a better job of helping us detect and avoid situations where our natural decision processes may go wrong.

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Image credit: cake by robokow