Enterprise Decision Management - a Weblog: October 2006 Archives - BeyeBLOGS.com

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October 31, 2006

Speaking on personalization at Content Week 2007

I am presenting on Extreme Personalization for Markets of 1 at Content Week 2007. The session will cover developing micro-segmentation and other advanced analytics, technologies for personalization such as business rules, collaborative filtering and how to deliver the right content, at the right time, through the right channel to deliver personalized experiences.

The show has a blog also.

Technorati Tags: business rules, customer experience, Customer management, personalization, precision marketing, predictive analytics

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Posted by James Taylor at 3:16 PM | Comments (0)

Precision marketing with EDM

I saw an article by Leslie Ament over on DM Review today - "The Precision Marketing Imperative". Leslie introduces some of the key concepts behind precision marketing and has this great definition

Driving continuous performance improvement through the use of personalization, segmentation, analytics, rules-based interactions, customer profitability scoring, decision-trees and/or closed-loop marketing planning and execution processes.

For those of you paying attention to this blog you will see that enterprise decision management is a great way to approach precision marketing. Not only does it include the use of business rules (including decision trees)and analytics, but it enables fine grained segmentation and deep personalization by moving from an environment where a single decision is taken about a campaign to one in which a decision is taken about how to interact with each customer. This focus on the automation and improvement of operational decisions is what EDM is all about and precision marketing is one of the growth areas for this approach.

There's a bunch more on marketing related topics on this blog and my colleague Jeff Zabin (who wrote a book called Precision Marketing) has a blog also - Pareto Rules - with lots of posts about this topic including this one. I also blogged about a previous article Leslie wrote on leveraging customer intelligence.

Technorati Tags: analytics, business rule, business rules, customer experience, personalization, precision marketing, Aberdeen

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Posted by James Taylor at 11:49 AM | Comments (0)

October 30, 2006

Building a nimble organization with EDM

Hugh Taylor (no relation), with whom I am giving a webinar on "Agile Compliance" tomorrow pointed me at a McKinsey report "Building a nimble organization" in the McKinsey Quarterly (subscription required). This McKinsey report defines nimble organizations as having agility and speed - agility being about changing direction fast (new strategy, new tactic) while speed is about executing on these. Often business agility is considered the combination of these (for instance Gartner defines it as a set of steps: Sense, Strategize, Decide, Communicate, Act) and certainly I tend to include speed and agility under the heading of "business agility". While the respondents clearly think this is important but are not sure what to do about it. As the report says

Executives around the world overwhelmingly agree that the agility and speed of their companies are urgent business issues
but
There is no consensus among executives on which organizational and behavioral barriers most impede a company's agility and speed.

Interestingly only a tiny 7% think IT is a contributor to this kind of agility, an astonishingly low percentage. As the report says:

State-of-the-art IT is not considered particularly important for addressing the issue.

This contrasted with some of the barriers respondents identified, many of which seemed to me to be ones technology could be used to overcome. Respondents listed barriers like overly centralized decision making, a tendency to refer decisions up and an inclination to over analyze. These three barriers can all be addressed, at least somewhat, with a technology-enabled Enterprise Decision Management (EDM) strategy. For instance:

Automation of operational decisions using an EDM approach pushes decision-making authority to the point of contact with a customer, avoiding a need to refer decisions to some central or higher authority.
An inclination to over-analyze can be partly addressed by not presenting information to employees but instead presenting conclusions or actions. If I am being given a ton of information about a customer and trying to decide what to do I can spend a long time slicing and dicing the information. If, instead, I get a set of recommended actions to take then I can act more rapidly.

In fact the report identifies one area that got broad agreement that can be delivered using EDM:

A broadly favored mechanism for fostering agility and speed is establishing a clear link between corporate strategy and employee performance goals.

Now I have written before about how EDM drives strategic alignment by linking corporate strategy not just to employee goals but to their actual actions. This has an added benefit of enabling corporate strategy to be linked to automated systems as well as those that involve people, improving a company's consistency (something often sacrificed in a drive to become more agile). It also allows a strategy to be implemented operationally while remaining confidential. Lastly the report did not identify a lack of timely performance information as an issue - perhaps because agility is more about turning your performance management information into useful action.

Technorati Tags: business rules, decision automation, EDM, Enterprise Decision Management, McKinsey

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Posted by James Taylor at 9:39 AM | Comments (0)

October 27, 2006

Business Intelligence 2.0 and Enterprise Decision Management

I have been reading a few things on "BI 2.0" and it made me wonder about the phrase and about the differences, or similarities, between BI 2.0 and EDM. I know Charles Nicholls of SeeWhy and read his nice little eBook. You may have seen SeeWhy in this Computerworld article or this ebizQ one (complete with a podcast).

I poked around and read a little about Celequest (with whom I have met) and Neil Raden's nice article "Bye-bye BI" in Intelligent Enterprise. I also read Charles' blog (though he has been quiet of late) and Diaz's (similarly sparse). Finally there was the classic research approach now taught in elementary school - I googled it.

Anyway, the upshot of all this is that there seems no broad agreement on what BI 2.0 is, though there are some characteristics that many people think it has. While these overlap with Enterprise Decision Management somewhat they are not the same and I think it is worth exploring it the similarities and differences a little.

First, let's see what the widely discussed BI 2.0 characteristics might look like:

BI 2.0 integrates events
The inclusion of events as something to be tracked, analyzed and used is widely agreed. We see discussions of "event-driven BI" to analyze streams of data, keep running totals without an intermediate storage mechanism.
BI 2.0 delivers insight
The need to deliver insight not information or reports comes up a fair bit - the idea that events or data are not interesting but insights derived from them, especially insights derived rapidly, are.
BI 2.0 delivers action without intervention
Several mentions of a more automated handling of the consequences of insight - the idea of taking corrective action without human intervention.
BI 2.0 is Real-time
Probably the single most agreed feature - all of this must be in real-time or close to it. There is a lot of talk about reducing all aspects of latency close to zero
BI 2.0 is based on SOA and Web 2.0
Like most things new BI 2.0 is expected to be service-based and Web 2.0 technologies are expected to impact the UI for BI 2.0

Much of this seems similar to discussions of operational BI. For instance, Neil Raden describes operational BI in his article:

"Operational BI or, more accurately, operational analytics, must be as lightweight and configurable as services. Grabbing a piece of historical data from a data warehouse, aligning it with current information from an operational process, perhaps dynamically generating a forecast based on trend analysis or even a stochastic process like Monte Carlo Simulation to produce a range of outcomes--all these activities must happen transparently and in near-real time. "

What we see is a focus on what you might call intelligent processes - ones where actual events drive responses in real time that rely on analysis of both data and events, particularly predictive analysis. Now both Celequest and SeeWhy seem to be taking what I would call an Enterprise Decision Management or EDM approach. The Celequest website explicitly talks about their server being implemented using a mix of analytics and business rules while SeeWhy must have some capability to execute rules to decide which alerts to send/actions to take when its real-time analytics come up with predictions that need responses. That said, they are also both focused on event-driven decisioning rather than "in-process" decisioning.

So how does BI 2.0 compare with EDM? Well EDM is likewise focused on delivering and acting on insight, often in real-time. EDM is service-oriented with its focus on decision services. Where they differ is really in three areas:

EDM is a balance between analytic insight and explicit knowledge/regulations.
BI 2.0 seems to be more focused on the analytic insight piece with rules (knowledge, regulations) relegated to a secondary position
EDM separates out the business decision-making completely from the context
This allows decisions to be reused in processes, legacy systems, in response to an event etc. BI 2.0 seems very focused on event-based triggers to the exclusion of other kinds of decisioning.
EDM is focused on decisions as a corporate asset
BI 2.0 is not.

I have blogged before about CEP(Complex Event Processing) and BAM (Business Activity Monitoring), both of which seem BI 2.0-related. In each case I believe that the decisions need to be externalized and managed so they can be used and maintained and improved independently. Let's end with another quote from Neil:

"Facing a global, externalized business environment, leading organizations must push beyond conventional BI and data-warehousing approaches and seek adaptable, agile solutions"

I think the products focusing on BI 2.0 are some of what you need for these "adaptable, agile solutions" but I think EDM is needed too.

Technorati Tags: analytics, BI, business intelligence, business rules, Celequest, decision automation, EDM, Enterprise Decision Management, operational BI, predictive analytics, service, SOA, SeeWhy

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Posted by James Taylor at 10:34 AM | Comments (0)

October 26, 2006

Article on SOA and business rules

I recently wrote an article on SOA and business rules for Thomas Erl's new magazine website SOA Magazine. Thomas is well known as an author on SOA and the site has some great articles. You can subscribe to an RSS feed for the articles too.

Technorati Tags: BRE, BRMS, business rule, business rules, service, SOA

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Posted by James Taylor at 2:09 PM | Comments (0)

Agile Compliance - upcoming webinar

Hugh Taylor and I are presenting Agile Compliance with Rules and SOA at an Intelligent Enterprise TechWebCast.

I look forward to "seeing" you there.

Technorati Tags: business rules, SOA, compliance

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Posted by James Taylor at 1:12 PM | Comments (0)

If you think people buy from people, think again

Interesting presentation by Henry H. Harteveldt of Forrester on "Creating Emotionally Engaging Digital Experiences" at the Consumer Forum 2006

DigitalChannels

What strikes me about this is the extent to which electronic interactions are going to drive the customer experience. This proliferation of electronic channels and the increasing use of them by customers, including potentially your best customers, means you had better have a way to control and improve these interactions. Automating key customer treatment decisions, using an enterprise decision management or EDM approach, is a great way to do this.

You can use embedded analytics to target customers more precisely to get better results - precision
You can use business rules to make sure it is easy to constantly change and adapt the decisions as you learn what works or need to respond to changes - agility
You can control a single point of decision across channels so that customers get the service they deserve (and that you decide to give them) regardless of the channel they choose - consistency

Increasingly your customers are going to buy from your systems, not from your people. Make sure your systems make the same kind of decisions you train your staff to.

There's a lot on this topic in the CRM/Customer Service section and I presented about this recently for the Teradata Partners Conference.

Technorati Tags: analytics, business rules, CRM, customer experience, decision automation, EDM, Enterprise Decision Management, Forrester, predictive analytics

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Posted by James Taylor at 11:23 AM | Comments (0)

October 25, 2006

Poor decision-making has consequences

Teradata conducts an annual survey around analytics. This came out a while back and was summarized in a press release - More Decisions, More Complexity, More Data: Teradata Survey Validates Global Phenomenon. There were some conclusions in this report that I found fascinating and so I thought I would blog about it. I picked the best time - it is a while since the press release so it's not timely and it is too early to get the printed survey from Teradata. This was not designed to be inconvenient, it's just when I got around to it.

So, some key findings and my thoughts about them:

Data volumes are increasing massively - over half of respondents saying that data volume is doubling or tripling over the previous year
To me this means automate or die. Data volumes are going nowhere but up and it's going to get harder and harder for people to effectively use all this data. One of the great things about computers is a much greater capacity for managing volume so why not turn all this data into insight/actions that can be executed automatically?
One common response to this extra data is to add staff
I suspect most of this was to handle the data management itself but if companies are adding staff to try and process the extra data, that's not going to scale. This data is only going to be useful if it can be applied to business problems and the volume and volume growth mean that this application will have to be automated.
According to almost 40 percent of respondents, front-line staff is increasingly making critical business decisions
A core concept of enterprise decision management is the empowerment of front-line staff to make analytically-sound decisions but to do so without requiring them to become analytic sophisticates or BI tool experts. If front-line staff are making customer treatment decisions then they are likely NOT making them as well as they could because they don't have the analytic skills, or time, to analyze what all your data is telling you. Why not automate this insight and deliver decisions to the front-line so they can focus on customer relationships?
Ensure that the entire organization consistently executes against strategy
One of the biggest problems in this is the need to keep some elements of strategy, and much customer data, confidential or at least tightly controlled. By using this strategy and data to inform automated decisions, you can implement the strategy in a flexible, high-performance way without requiring everyone to know the strategy or see the confidential data. True strategic alignment.
The top five casualties of poor decision-making are customer loyalty, company reputation among customers, profits, company productivity and customer service
The clear problem of poor decisions is the impact on your relationship with your customers. Making sure that customers are treated correctly and that they have a good experience, one that won't cause them to leave, is key. Integrating analytics and process will deliver this.
The importance of real-time information is a five-year trend, and this year, eighty-five percent of respondents said that decision-makers need more up-to-date information than in the past
So more and more people need to take more and more decisions with more and more data in less and less time. Hmm, sounds like these people need to automate some of this...
As a Teradata executive said "when you have the customer on the phone or in front of you, or you have a truck in the loading dock, you want to make sure that the right data is available so that the best decisions can be made on the spot," . The data is interesting, the decision is what matters. Helping people make decisions is one approach (BI) but automating these decisions so they can be managed and improved (EDM) is another. EDM will let you capitalize on the customer insights that are now available to you and help address some of the latency in getting from data to better customer decisions.

If you want a copy of the study you will be able to get it from Teradata in a couple of weeks - probably from your account manager/sales rep. Fair Isaac is a Teradata Partner and I have blogged before about the overlap between their concept of EDW and EDM.

Technorati Tags: agile, analytics, BI, business intelligence, business rules, composite application, CRM, customer experience, Customer management, decision automation, EDM, Enterprise Decision Management, operational BI, predictive analytics, data warehouse, teradata

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Posted by James Taylor at 2:38 PM | Comments (0)

October 23, 2006

Automating and improving pricing in banking

I saw this piece on "Best Practices in Customer Management: Some New Methods Breaking Out" by Kathleen Khirallah over at Tower Group. Kathleen is always a thoughtful writer and this piece was no exception. One of the take-aways struck me particularly:

"If there is one factor that has hampered banks' ability to be customer-centric and proactively manage their relationships with customers, it is their reliance on a "one-size-fits-all" approach to the mass market."

Now Kathleen talks about this in the context of pricing for this paper, but I think this is a valid criticism of most banks about almost every aspect of how their interact with customers. But let's stick to pricing. Kathleen discusses why banks find it so hard to compete with pricing or even to use pricing as part of an overall strategy. She says:

"Banks' disinclination to compete on price is generally tied directly to the paucity of analytics and rigor in their pricing computations".

Essentially pricing can only get more sophisticated as more analytics enter the decisioning process. Simple segmentation analytics will help but any serious attempt to manage pricing in a more sophisticated way will involve multiple models (risk, propensity to buy, propensity to use credit, retention risk) and do some tradeoff between them. In addition pricing decisions will still need rules as there are layers of regulation and policies that must be applied around the models. The key element to get started is that Banks need more finely grained segmentation for their pricing. Most of them already do a great job of segmentation for risk, credit line management and so on but they lack this approach in pricing. They don't have a comprehensive pricing strategy that reflects the sensitivities and desires of customers. As Kathleen says:

"If there is one factor that has hampered banks in their ability to be customer-centric and proactively manage their relationships with customers, it is their reliance on a one-size-fits-all approach to the mass market".

So how would you tackle this from an Enterprise Decision Management approach:

Focus on the pricing decision made for a product and a customer as a specific operational decision
As distinct from saying the decision is a strategic one as to how to price a product line.
Build analytic models for various aspects of the customer

Propensity to buy
Price sensitivity
Lifetime value
Credit Risk
Retention Risk
...

Build some kind of decision model to show how these aspects interact and are constrained
Offline, optimize the decisions based on this model to come up with the best rules for pricing for each customer segment
Do some what-if analysis and flex your constraints to see what the impact is of these changes. Come up with the best set of rules for pricing based on this modeling.
Deploy these pricing rules into all the systems that need them, ideally using centralized decision management

Fair Isaac approaches this with a product we call Decision Optimizer and an associated methodology called Strategy Science. To be fair this has not been widely used in pricing yet but it has worked well in credit line management and fraud referral strategy design. Another company taking a similar approach is Earnix who provide a service to offer the best or optimal price when a customer (new or existing) asks for a product price based on this customer’s predicted price sensitivity and propensity to buy and then generate a rate card (rules for rating essentially) that can be deployed.

Finally one last comment from Kathleen:

"A few forward-thinking banks have recognized the importance of customer satisfaction and now report and measure satisfaction with the same rigor that is typically associated with risk management"

I think this reveals a key point - that even customer management decisions have an element of risk. There is a risk implicit in using resources on this customer that could be used on that one. There is a risk in a price for a product in that it might retain unwanted customers or deter potentially profitable ones. Banks have long taken a fine-grained and analytically-rich approach to risk management. Time to do the same for all aspects of customer interaction.

Technorati Tags: analytics, business rules, Customer management, decision automation, personalization, predictive analytics, pricing, Tower

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Posted by James Taylor at 10:45 PM | Comments (0)

October 20, 2006

Article on analytically-driven processes

There's a great article on Coming Soon: The Analytically Driven Process in the DM Review newsletter this week.

Of course, I wrote it so I would say that wouldn't I...

If you like it you might like this post from Gartner ITxpo and if you want some background on analytics try this article on predictive analytics.

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Posted by James Taylor at 9:09 AM | Comments (0)

October 19, 2006

Delphi Business

I have been attending the Delphi Business amp; Process Innovation Summit this week and blogging over on ebizQ. Here are the links if you are interested.

Nice conference, lots of interesting stuff.

Technorati Tags: business process management, decision automation, EDM, Enterprise Decision Management, innovation

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Posted by James Taylor at 11:00 AM | Comments (0)

October 18, 2006

New podcast on EDM

Outlookseries_2 I was interviewed on Officer Outlook again recently, this time on Enterprise Decision Management (EDM). You can listen to it online on the Outlook Series site or download it as a podcast from Decisions Podcast.

BTW you can subscribe to the Decisions Podcast feed here.

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Posted by James Taylor at 9:14 AM | Comments (0)

Shameless Commerce - a European EDM conference

For those of you in Europe you might want to check out the forthcoming conference on decisioning that Fair Isaac is going to be running - InterACT Lisbon, February 27th - March 2nd. InterACT involves presentations from Fair Isaac experts (including yours truly) as well as some of our best clients from around the world and is the only conference focused on solutions for Enterprise Decision Management. It's been running since 1976 and more than 10,000 attendees have come over the years.

InterACT will cover advances in predictive analytics and decision technology as well as ways to apply Enterprise Decision Management in financial services, insurance and so on. There are case studies, product demonstrations and presentations on future directions all designed to help you apply predictive analytics and business rules for greater efficiency and profitability.

On top of that, Lisbon is supposed to be lovely in February :-)

lt;Shameless commerce endsgt;

Technorati Tags: analytics, banking, business rules, decision automation, EDM, Enterprise Decision Management, fair isaac, insurance, predictive analytics, interact

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Posted by James Taylor at 8:49 AM | Comments (0)

October 17, 2006

Free webinar with Tom Davenport on analytics

The folks at Aquent let me know that they are sponsoring a webinar with Professor Tom Davenport (about whom I have blogged about his writings and about his presentations) author of “Competing on Analytics: Move Faster, Accomplish More, and Avoid Mistakes by Learning From The Best”. The seminar is on October 31, 2006 @ 1:00 pm EST. Tom will discuss what data-driven marketing is (and isn’t), the broad strategies and specific tactics these early adopters believe were essential to their success (and what they’d do differently next time), and how marketers can be professionally successful in these tumultuous times. You can register at http://aquent.com/webinar

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Posted by James Taylor at 3:01 PM | Comments (0)

Rules Management Solution Powers Customer Incentive Program

A case study as published in Enterprise Systems Journal about Avnet - Rules Management Solution Powers Customer Incentive Program. This case study covers how a Blaze Advisor customer built a rebate management system. A great story of a project paying for itself in just a few months.

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Posted by James Taylor at 9:42 AM | Comments (0)

October 13, 2006

Congratulations to our friends at Ohio Casualty

Ohio Casualty was honored with Elite 8 status this year by Insurance and Technology magazine. Ohio Casualty are a long time Blaze Advisor business rules customer and use Blaze Advisor to validate data entered in the PARIS XP system described in the award.

PARIS provides a web-based front-end to the end-customers (mostly agents) where new policy information is entered. As new information is being entered, PARIS XP calls rules services at pre-determined break-points to validate information entered against underwriting rules managed in Blaze Advisor. As a result of this validation process, the rule services may send back "messages" that can be broadly categorized as; “bind”, “do-not-bind”, or “decline”. Agents can then write a policy, refer it for manual underwriting or decline it. After the underwriting process, PARIS XP calls a rating engine and calculates the policy premium.

By using Blaze Advisor to deliver rule services to the system Ohio casualty can manage the underwriting rules explicitly, make changes more easily and deliver consistent underwriting decisions across their agents.

Technorati Tags: BRE, BRMS, business rule, business rules, decision automation, insurance

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Posted by James Taylor at 3:30 PM | Comments (0)

Predictive Analytics in the news

I was struck today by three pieces on predictive analytics

First there was a piece in Computerworld "QuickStudy: Predictive Analytics". This was a pretty nice introduction to predictive analytics (though not as good as my FAQ on the subject of course). There was a really nice summary sentence, however:

Ultimately, businesses want predictive analytics to suggest how to best target resources for maximum return.

Absolutely right - its all about making the best possible use of your resources. I did have one criticism of the article. You could follow all 5 of their best practices (see page 2) and still fail to get any value. The missing best practice is deployment. So read the article, but add this item to the best practices list:

6. Ensure deployment of the models
The best model in the world will not help if you never get it into production. Use technology and processes that focus not just on building a good model but also on making sure the model can be and then is deployed.

Then I saw Oracle's announcement about Sigma Dynamics and Gartner's comment about it - Deal Enables Oracle to Pursue Wider 'Decisioning' Opportunity in which Gareth Herschel says he feels this moves Oracle into "decision management" and then goes on to explain that Sigma Dynamics takes what I would call an Enterprise Decision Management approach by combing rules and analytics, albeit in a specific area. Oracle's website says that

Sigma Dynamics' Real-time Decision software combines customer insight and business requirements to instantaneously make the best recommendation in each customer interaction and operational decision by intelligently adapting to continuously changing information.

Sounds like a localized implementation of an EDM approach to me. Glad to see Oracle joining the party.

And finally, of course, Fair Isaac announced a new release of Model Builder. Version 3.5 now offers Data Spiders™ - genetic algorithm-based technology to help analysts overcome the tedium of data preparation by searching raw transaction data, generating characteristics and finding the most powerful predictors. 3.5 also adds the ability to read and write DBMS and SAS data as well as enhanced support for Predictive Model Markup Language (PMML).

Predictive analytics, like business rules, seems all over the news these days.

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Posted by James Taylor at 1:56 PM | Comments (0)

October 12, 2006

Live from Gartner Symposium ITxpo - BPM Technology Selection: How Solutions Are Evolving

I am attending Gartner Symposium and ITxpo this week and blogging as I go. Last session before I have to leave for the airport.

Jim Sinur presented on BPM Technology Selection: How Solutions Are Evolving

BPM requires a methodology or approach as well as technology but this about technology. In business today Six Sigma and Lean Six Sigma both increasingly used and both focus on continuous improvement and BPM can really help develop this. Jim outlined the development of BPM from just modeling procsses, to modeling and executing, to integrating people and systems and monitoring all of this. The market is now seeing what Gartner call a BPM Suite with new features include optimization, in-line simulation, business rules, business rules management and scenario management for rules.

Jim talked about the growing intersection of rules and analytics, what I call Enterprise Decision Management or EDM, and I could not agree more. He also talked about goal-directed BPM. I already see some work around goal-directed decision-making (to come up with optimal decision rules) and this could certainly drive goal-directed processes. Business people meanwhile will become more and more involved in the definition and simulation of processes (and rules) and the advent of widespread SOA will reinforce BPM very effectively - I wrote about the intersection of BPM, SOA and CEP before. In this vision BPM technology composites and orchestrates services to create business value and cut across silos. Jim talked about this view of composite applications and the widespread use of rules to add value to standard components. This is where all this technology goes.

Well that's, I am out of here. Back to regular blogging next week.

BPM Suites make lots of things explicit:

Processes becoming explicit and being managed more and more by business professionals. Jim talked extensively about using a business rules engine to deliver decision-agility to the process without having to change the process. I wrote some stuff on Gartner's approach to agility and how to achieve it that includes consideration of both rules and process management for agility.
Document and imaging routing becoming explicit so as to make documents available in a process context.
Modeling makes the processes and their dependencies explicit so they can be simulated and managed. People really want a common modeling approach and a way to share models but nothing yet arrived.
Integration brokers make system to system interactions explicit and makes data and transactions visible. Most of these lack rules as part of this - like webMethods for instance, who OEM Blaze Advisor.
Portals make user navigation explicit and manageable and can guide best practices and bring multiple work threads together.
Rules to manage decision and diagnostic logic - need rules in services, integration, decisions, more places. These rules are easier to share and change and so on. I wrote about different ways to build decision services and to use rules before. Jim also feels that rules are the right way to help someone take action when dashboards tell you that somethings up. I wrote about this in the agility piece above and in an article here on putting performance management to work.

In terms of why use technology of this kind he made some points:

System change requests spiking but only about 35% of rules are changeable enough and about 20% of them will be managed by IT leaving 15% to be managed by the business. Personally my experience is that everyone ends up with more changeable rules that they expect.
Exception handling must be improved and thus people must be managed as part of this
CRM interactions, both self-serve and customer-service processes are more and more key
Compliance and oversight imposing constraints that must be managed without a loss of agility
Outsourcing will be easier as you can control the critical decision nodes within a process
Business users must control more

In the future you see

BAM or Business Activity Monitoring (I blogged about EDM and BAM)
Smarter user interface components (SmartForms perhaps)
Pre-built components and templates (like Fair Isaac's Decision Accelerator for origination perhaps)
Predictive modeling (presumably injected into processes by analytically enhancing rules-based decisions)

Technorati Tags: BPM, BPMS, BRE, BRMS, business process management, business rule, business rules, decision automation, EDM, Enterprise Decision Management, Gartner, predictive analytics

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Posted by James Taylor at 11:45 AM | Comments (0)

Live from Gartner Symposium ITxpo - Impressions from the expo

I am attending Gartner Symposium and ITxpo this week and blogging as I go. This post is based on my reaction to exploring the show floor this year.

I have to say I was surprised by the lack of "energy" around both Business Process Management (BPM) and Business Intelligence. We are the only large sponsor that really intersects with either category. A handful of BPM vendors (FileNet, Lombardi, Global360, ) were present, mixed in with the business applications folks. Only one other rules vendor (ILOG) was present and although the BI vendors were mostly present (SAS, BusinessObjects, Cognos) none was terribly visible.

Oracle was particularly noticeable in its absence from the Enterprise Applications and BI sections while SAP was also fairly subdued. Sun was also missing.

The content mana