I am involved in two great decision management shows this year and I wanted to tell you about them.
First up is InterACT, Fair Isaac's show on decision management and analytics, April 27-30. Even if you aren't a Fair Isaac client you should check out this show. It's at the Palace Hotel in lovely San Francisco and is an opportunity to hear Ian Ayres, author of Super Crunchers and attend one of the best analytic symposiums to hear about some leading edge analytic techniques and approaches. There are lots of sessions for Financial Services companies on how to cope with the current banking crisis - sessions on managing highly indebted consumers, risk management, helping the unbanked, the mortgage crisis, better collections strategy and for Insurance companies who can find a whole track on claims, underwriting, customer service and marketing in the new world of insurance.

John Rymer of Forrester, one of my favorite analysts, is speaking on dynamic business applications, a really interesting area and there are a number of sessions on detecting, managing and controlling fraud from internal and external threats. The growing array of regulations - Basel II and others - are covered so you can grow through your response to regulation not collapse under its weight and scoring, of course, will get a thorough working over so you won't be confused about the benefits and limitations of scoring.

I will be there blogging and I want to meet you. I am offering a discount for readers - just enter the discount code SFJT when you register and get the unlimited registration for just $1,345. This is a great deal! You can register here and get more information on the event here. I highly recommend the show and I hope to see you there.

The second show is the all-new Enterprise Decision Management (EDM) Summit of which I am a co-chair (with my business partner and co-author, Neil Raden). This show is running October 26-30 alongside the established Business Rules Forum and will be show casing case studies on using decision management for competitive advantage, how to compete with analytic decision-making, how decision services enhance SOA and much more. Registration is not open yet but you can put yourself on the mailing list here. This is the first large-scale conference with a decision management theme and we are assembling a great set of tutorials (SOA, agile, business rules, data mining, decision management and optimization among others) and speakers. Look for me to blog more about this in the coming months but get on that mailing list now.

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I thought it would be fun to highlight my 20 most popular posts from the last couple of years so here goes:

1. Keeping Predictive Analytics and BI on separate tracks
   
2. If IT wants to alter outcomes, it needs to automate decisions
   
3. Business rules, events and processes
   
4. Getting a competitive advantage from your data
   
5. Achieving Agility - some notes after Gartner
   
6. Introducing business decision management
   
7. Here's a way to put analytic solutions in the driving seat
   
8. Decision Technologies and Active Data Warehousing
   
9. SOA and Business Rules, perfect together
   
10. Business rules, routing rules, event rules
    
11. Decision Services
    
12. Decision management is critical to event driven architecture
    
13. Decision Management - another way to get the business to care about SOA
    
14. Marketing Analytics in a Post-Web 2.0 World
    
15. Little known ways to improve customer experience
    
16. More on rules and event processing
    
17. Business rules, desktops and knowledge buses
    
18. If dashboards are the end game, kill me now...
    
19. COBIT, SOX, compliance and business rules
    
20. Call for Presentations - the new EDM Summit
    

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Joe pointed me to an interesting article in his recent post discussing the power of data, and analytics, to replace "gut instinct" in business. This follows my post earlier this week on getting a competitive edge from your data.

I have to agree with this point of view - clearly companies now have so much data about what works and does not work and so many tools for understanding that data that there is no longer any excuse for just trusting "gut instinct"

Clearly the past is not a perfect image of the future and some things that might work well may not be allowed so it is not just a question of doing analytics on your data - you must use the kind of analytics that make predictions and model uncertainty (predictive analytics). You must also combine them with rules derived from regulations, policies, best practices etc and constantly challenge them with new and potentially better approaches - ongoing randomized testing or adaptive control.

One of the values of a more automated, data-centric approach is that it helps address some of the well known decision making traps because it is not clear that experts REALLY do better when it comes to making decisions. While it may be scary to let machines take decisions, it need not be.
Finally, you might also enjoy my review of Blink

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I saw this post from Steve Jones on Change the business not the package and he made the very valid point that even if you are buying your packaged software in the form of services - a service-oriented package if you will, you should resist the temptation to customize it to death. Yes, perhaps SOA will make it easier, but not really. In this context, however, decision management can really be your friend.

One of the best ways to customize a package is to inject custom decision making into it. Most packages are pretty dumb (as noted in this post) and don't make many decisions being more focused on the create, read, update, delete logic necessary to manage your data. Adding decision services not only makes them smarter, it adds services designed to be easy to change and adapt. An SOA-based package makes this a lot easier. Building a composite application that combines the packaged services with easy to customize decision services might just give you the best of both worlds.

I have blogged about how enterprise applications can be enhanced in this way before and discussed how a process-oriented approach may not work for you here.

Technorati Tags: business agility, business rules, decision management, decision service, enterprise applications, SOA

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Over on the decision strategist there was an interesting post - Can Decision Systems Help Us Make Better Decisions? This was a thoughtful and interesting response but I am still going to have to disagree with a couple of points. Firstly the post assets that automation of decisions has not yet arrived. Yet many industries, especially those that must make risk-centric decisions, have long used automation to circumvent errors and bias. The use of rules and analytics to automate credit decisions, insurance underwriting and fraud detection is well established. The reality is that these systems make far fewer errors, are much faster and show less bias than the manual systems they replaced. It is true, however, that we have not reached the point where systems can do this for all decisions (though we get closer all the time). The post goes on to say:

The answer can be systematically determined based on several variables to find the maximum customer satisfaction for the lowest cost.The problem is that these systems remain inflexible.

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Mitch Betts pointed me to an interesting Babson piece - Creating Great Products with Apple's Steve Wozniak, Inventor of the Personal Computer. One particular answer Woz gave caught my eye:

Wozniak: I think design and development should always be done from a point of view that believes the human being is worth more than the technology. You just have to have it in your head that you will apply a lot of effort to bend your hardware and create your software design so that the user has a nice easy flow in using this product. In this way it fits their life as they live it now. The opposite way is where someone decides to put in all the functionality in a way that causes the user to modify the way they do things. This difference is where the huge value is, at least for Apple.

• An ATM should reflect how this particular customer uses ATMs not present a generic approach.
• A call center operator wants to make a cross-sell offer to a customer to earn a bonus. Tell them what the most effective one is.
• A nurse is treating a patient in a hospital, tell them the right dosage and flag the potential interaction caused by a new prescription
• A prospect on your website wants a price, not a form to refer them to someone
• A customer wants coverage now, not in a few days time

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Michael Hugos over at CIO magazine had an interesting post today - The System Builder Drives IT Agility. He makes five suggestions on which I thought I would follow-up:

• Understanding business operation - shared understanding presumably despite the different perspectives of business and IT
• Inclusive process - one like concurrent business engineering, for instance
• Tolerate not knowing - both because you need to investigate the issues and because those issues change
• Simple underlying pattens - rule templates, for instance, to empower business users to maintain their own rules
• Simple combinations - for instance, when decisioning is called for use decision services to keep everything clean and packaged

He also referenced this one - The 30-Day Blitz, IT Agility in Action - and I think business rules and decision services are often a very effective way to add value to existing systems quickly and without completely re-writing the systems concerned. Check out this legacy modernization story, for instance, or posts in the legacy modernization category.

Technorati Tags: agility, business rules, change time, CIO, CIO Magazine, decision automation, decision service, Michael Hugos, business agility

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<shameless commerce>

As some of you know by now I have been working, with Neil Raden, on a new book. As the files shipped to the printers today I thought I would take the opportunity to shamelessly plug the book here on the blog. The book's premise is that much of today's existing technology has the potential to be "smart enough" to make a big difference to your organization's business and that current business trends are forcing you to build smarter systems. Like this blog, the book discusses how focusing on decisions as distinct opportunities for improvement, you can use established technologies in a new way to solve problems and create competitive advantage.

You can pre-order it here from Prentice Hall (there is even a blog discount coupon code TAYLOR7962) or from amazon.com here (amazon.com has not yet decided what price it will charge).

The book has a companion site too - http://www.smartenoughsystems.com where you can subscribe to news about the book/authors and read the testimonials we got. Over time we will add more useful links to the site.

If you are not yet convinced that you need to read the book, why not try the digital shortcut "Why you Need Smart Enough Systems". You can buy it online from Prentice Hall  for less than $5! If you need to be convinced that you need to use decision management to make your systems smart enough to be useful (or if you have colleagues or customers who don't understand why they should apply the techniques we talk about on the blog), you will find this a good read.

</shameless commerce>

Technorati Tags: adaptive control, business rules, data mining, decision, decision automation, decision service, decision service, EDM, enterprise decision management, optimization, predictive analytics, Smart (Enough) Systems, smartenoughsystems

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I saw this post on John Hagel's blog - The Power of Power Laws. It's a great piece, very thoughtful and I wanted to link to it. I wish I had something brilliant to add to it but I don't, though I get the feeling that decision automation should matter given his premise.
Oh well. Check out this post on hearing him speak before as well as these on the Long Tail (and the book review) and my review of his last book on my other blog.

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Ian, the other blogger over on www.edmblog.com, sent me this little snippet today:

68 percent - Proportion of the IT budget that average North American companies used to support existing software and hardware in 2006, according to Gartner. About 19 percent went to adding capabilities to keep up with company growth, and 13 percent was spent on technology to propel the company into new markets or sell products and services in new ways.
Source: Baseline

Wow. So if you actually need to deliver any innovation from your systems, you need to free up some of the money you are spending on application maintenance. Part of the problem here is poor maintenance processes. The use of business rules to modernize some of your legacy applications can be very effective. A great example of this was the California DMV who reduced the maintenance cost of a big legacy system by renovating just part of it using business rules.

Technorati Tags: application maintenance, business rules, innovation

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Well it's Christmas time and I am going to take a break from the blog for a week or so. See you after the new year.

Happy Holidays

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Recent posts, such as this one by KC Jones on TechWeb talk about a peak in blogging, implying that blogging is going to peak and then die down. Now it is hardly surprising that the blog market would grow more slowly as it gets bigger. Additionally, the participation percentages, that seem to contribute to the "end of blogging as we know it" tone were actually pretty good. For instance, 2% regular contributors and 10-15% occasional contributors is actually better than most "historic" online communities where, as Jakob Nielsen, says

90% of users are lurkers who never contribute, 9% of users contribute a little, and 1% of users account for almost all the action. (found on Tiara.org)

So this makes the blogosphere look pretty healthy, at least relative to other forms of online community. The flurry of articles on this made our own Elizabeth Book say:

I think collaborative communities that support virtual conferences for real business reasons, like Second Life, are going to start replacing blogs, but I think blogs still serve a very important purpose for thought leadership in specialized industries like ours. I don't think that good blogs, and people who excel at the blogging medium, are going away anytime soon.

Now as I recently participated in a tour of IBM's new island in Second Life, this made me think - did I see anything there that would replace my use of blogs or that I could even imagine doing so. Blogs are an asynchronous collaborative media where someone has knowledge or opinions they wish to share and through which they can engage a community in discussion. They are not tools for virtual conferences, interactivity etc. Places like Second LIfe, however, are designed for real-time interaction between people. Geographic distance might have been eliminated but the need to be present in time has not. On the other hand the overhead in transmitting know-how to an audience in SL should not be underestimated. Despite the significant effort IBM had put into their island, it was time consuming to learn very much about their technology. With the limitations in the technology today, a very limited experience is possible (recorded video/audio or typed messages and graphics). Attempts, like those in the Circuit City virtual store, to let you manipulate products through your avatar seemed clunky and would not give any sense of the design benefits or problems inherent in the product in RL (real life).

Before I write the whole thing off, though, I should not a recent statistic showing that 75% of adults prefer email to IM while 75% of teens prefer IM to email. Clearly my kids are growing up in a more synchronous world and prefer it to the asynch communications I like. They might, then, prefer to get information from an IBM avatar in SL than from an IBM blogger in RL. For now though the scalability problems inherent in synchronous communication (you all have to be there at once), the lack of an ability to search any kind of log/history/previous interactions and the limitations of the environment make me think that I am going to be writing my blog for a long time before I feel compelled to open an SL "decision management" island.

Technorati Tags: blog, Second Life, IBM

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One of the tactical gains often seen when decisions are automated is revenue gain at point of sale not from the targeting but from the simple fact of pushing decisions to the point of contact. This increased revenue comes because many people are not ruthless comparison shoppers and because pushing decisions to the point of contact can means closing the business at once. Take the example of insurance underwriting. Pushing this decision to the point of contact means eliminating the need for an underwriter to review the application so that the person actually interacting with the customer, typically not an underwriter, can make the decision. What about cross-sell offers for customers who only use your ATMs? Pushing decisions to the point of contact means making the ATM make the cross-sell. What about correctly identifying the spare part a customer needs? Pushing the decision to the point of contact means helping them identify the part for themselves on your website not making them send an email or make a phone call to someone who understands how the product is put together. All this comes down to using the automation of a decision to enable anyone, or any system, to make the decision. Manual decision-making, in contrast, often requires customers to wait or return later, risking that they will find someone else to offer them what they want. Pushing to close this gap can result in serious risk exposure if you rely on less well trained staff, or simply less experienced ones, to make complex decisions. Automating the decision enables those with expertise, and historical data, to ensure that the decision is appropriate and yet allowing it to be delivered at point of contact with customers.

Now one of the great things about computers is their speed. Not only can they do things fast, but the speed at which they do things keeps improving and the cost keeps declining. Automation of a decision can therefore cut the decision time to zero or close enough to zero for a human. Take a loan example. If I can decide on a loan in 3 days when my competitors take 5 that might give me a slight edge. But customers will still need to wait so the advantage is not great. Even if I can cut my time to a few hours I still don't have a huge edge. But if I can get my decision time to almost zero then I can give a customer an answer in the branch, on the phone, at the website. Customers like instant gratification - if the price seems OK they might well just take it. Cut the decision time to zero and you can capture more business.

Technorati Tags: decision automation, ROI

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How do you tell if your organization is ready for decision management? If not, what can you do to start laying the groundwork?

Fifth, Focus on operational decisions

One of the key facets of decision management is its focus on operational decisions. In order for decision management projects to be successful you need to get management to consider operational decisions as worth improving and amenable to improvement. While this may not sound hard, it can be. Some managers are very focused on "being strategic" or on "big picture" issues. Working on improving the small, incremental decisions that drive the business operations may not sound important enough to apply their time and energy. Additional it takes a certain focus to consider these decisions - one must stop thinking about macro-decisions like "campaign design" and start thinking about micro-decisions like "offer for this customer". Old habits can die hard and make this difficult to master.

One effective way to get management attention is to focus on the decisions, the operational decisions, that support a particular business strategy. Let's say the organization is trying hard to retain more customers. Many operational decisions, from routing calls to call center representatives to retention offers to self-service might contribute to customer retention problems. Showing executives that improving these operational decisions can have a direct impact on their strategic goals can get their attention. Perhaps even more effective is asking them how long they think it would take the organization to change to respond to a new strategy. Given how unresponsive to change many information systems are and how often decisions are redundantly spread between many systems, the answer may be distressing. Focusing on automating the contributing operational decisions can improve the alignment of operational systems with the business and so make changing, and managing, strategy more realistic.

Another issue that comes up as you start to use analytics in decision-making is a tendency for management to trust "gut instinct" over data. While this is a generally unhelpful attitude for anyone trying to introduce analytically-driven decisions it can be overcome more easily for an operational decision than for a strategic one. Think about it - who's "gut" is being used to make an operational decision? Not the CEO, not senior management, not even (probably) a highly trained professional but a low-level employee talking to a customer. Why would your management want customer-facing operational decisions made by such an employee based on their "gut instinct"? Most managers would, I suspect, prefer to have at least some degree of analytic support for these kinds of decisions. Finding stories about how important customers were put off by operational decisions made incorrectly can help focus management attention on the need to automate and improve these decisions and overcome a reluctance to trust the data.

In general you are going to need management support so try and focus on projects that have an impact on business areas that have management who "get it". Here are a couple of useful links:

• Operational decisioinng needs more than dashboards
• Welcome to Business Intelligence
• Operational Business Intelligence means Enterprise Decision Management

Technorati Tags: analytics, business intelligence, decision automation, innovation, operational BI, organizational change, predictive analytics, readiness

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How do you tell if your organization is ready for decision management? If not, what can you do to start laying the groundwork?

Fourth, Organizational Change

Automation of operational decisions can cause a fair degree of organizational change. Some roles will change - they will go from making large numbers of simple decisions to spending their time considering the overall patterns of decisions. Thus underwriters might go from spending most of their time considering individual policies to spending most of their time doing analysis of the relative success of agents or areas of the state. Advertising managers might spend their time on account management not on calculating ad prices. This change will mean that some people will go from being good at their job to being less good, and vice versa. This new focus will need to be articulated to staff and the implications managed. If staff reductions are not planned then reassurance will be needed that the computer is not going to replace people. If staff reductions are expected then this will have to be managed. Organizations that have a hard time managing this kind of change may want to start with projects that automate decisions not taken at all in the past (adding a cross-sell engine for example) or that are already automated poorly (a generic cross-sell embedded in the website for example).

Where staff are relying on the decisions made by a decision service and are responsible for passing it on to customers - such as a call center representative using a pricing engine - there may well be a reluctance to "trust" the computer's judgment. This is especially true if the staff have bonuses or similar tied to the effectiveness of the decision. One way to manage this is to implement the new decision service incrementally and make it available only to a small group of staff (those more willing to change) to show it works. Retrospective analysis can also be used to show how much more successful the organization would have been if they had used the new service in place of the old judgmental process. If this can be tied to statements like "you would have made X more money" then so much the better. Nothing succeeds like success so try and demonstrate success with a few or that the new approach would have been more successful than the existing one. Be prepared for initial concern no matter what you do - there will be a spike in complaints/appeals etc initially but if the decisions are sound it will wear off.

Customers getting automated decisions may be glad to get more done in a self-service way but will likely also feel aggrieved if they don't get what they want "because the computer said so". Managing this requires decision services that explain their decisions, at least to staff if not to customers. Decisions that say "no but" rather than just "no" will also do better. For instance, "you cannot have that product but you can have this one". Be sure to have legal review any decisions that are regulated or that have historically generated lawsuits over bias on the part of staff. Making sure the rules and analytics you use are defensible in advance will be easier than running around in the face of lawsuits. Again, introducing decisions incrementally and with explanation, especially when the decision is important to a customer (loan approval is, cross-sell is not) will be important and should be planned for.

Finally beware of counter productive incentives. Sometimes the sophistication possible in an decision management solution will overwhelm the performance and reward structure. For example, marketing staff may have objectives for both volume and response rate. A decision engine that dramatically improves the response rate may reduce the volume of offers mailed and this may cause people to miss their bonuses which will, in turn, make them unwilling to use the decision service. Where decision services are going to affect the behavior of staff, play out the impact you hope for of the decision service on their behavior and see if it increases or decreases their pay. If they lose out, but the decision service is making decisions that are better for the company, make sure this is addressed as part of the rollout.

Technorati Tags: business agility, business rules, decision automation, EDM, Enterprise Decision Management, innovation, readiness, organizational change

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How do you tell if your organization is ready for decision management? If not, what can you do to start laying the groundwork?

Third, Analytic understanding

A third area of readiness is going to be in terms of analytic understanding or sophistication. Delivering decision management solutions, especially the more advanced ones, requires analytic skills. There are a number of areas in which analytic readiness may be an issue.

Some companies will lack the necessary analytic skills completely. Where there is not a prior culture of analyzing data to try and understand the company and no history of using mathematical models there is unlikely to be any existing analytical staff. While one can be built it will probably be easiest to start by hiring external consultants to provide these skills. Fortunately many companies offer services to turn data into analytic models and, provided sensible due diligence is performed and the request is framed in terms of getting the analytic insight into a decision service not just developing a report explaining the model, all should be well. Over time, as analytic models prove their value, it may well be worth hiring in-house analytic skills. If you lack this kind of analytic skill in house then the first few projects should be those where rules (regulations, policies, expert judgment) dominate rather than data-driven insight.

Some companies will have plenty of analytic skills but will find them focused purely on reporting and analysis - Business Intelligence-style analytics. While these skills might be useful in an decision management context, a change in focus and an upgrading of skills will be required. Someone who can use a regression analysis tool to understand how data is trending has many of the skills necessary to build a predictive model that uses regression analysis but they need to learn how to apply them differently. If you have a BI Competency Center or other concentration of analysts you may find suitable people there to work with you on projects but you may not. Either way, make sure you engage these folks early in a project so that they can see how upgrading their skills and changing their focus will help demonstrate a better ROI from the BI/DW investments already made.

The last option is that there is a center of modeling excellence in the company but it is very narrowly focused. For instance, on risk modeling or in an actuarial group. While these resources will be ideal for projects dealing with their specialty it may prove difficult to get access to them for projects in other areas. Even if they can participate it may be hard for them to apply these skills to operational systems and to new domains. On the plus side you should be able to use them as a proof point for the overall value of modeling and analytics and that should make it easier to hire/contract with the necessary resources.

In general, unless you have an existing group of modelers developing models for your domain area, you are likely to be looking for outside help initially. If the analysts you use, inside or out, are not used to the decision management approach and expect to be able to deliver a report describing a model rather than work with you to deploy that model into a decision service then you will have a change management task ahead of you. Fortunately the data mining/analytic modeling community is increasingly aware that a model is no good unless it gets deployed.

Some useful links for you:

• Comparison of BI and Decision Management
• The value of using data not just understanding it
• How the embedding of predictive analytics can bring intelligence to processes

Technorati Tags: analytics, BI, business intelligence, data mining, decision automation, EDM, Enterprise Decision Management, innovation, operational BI, predictive analytics

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How do you tell if your organization is ready for decision management? If not, what can you do to start laying the groundwork?

Second, Data readiness

In order to derive insight from data you must first have data available. The accuracy, completeness and integration of the data you have will determine the quality of insight that can be derived. Of these by far the most important is the accuracy of data. Building predictive analytic models from inaccurate data or mining inaccurate data for business rules will be fatal - the results will build on the inaccuracies of the data and product inaccurate predictions.

Accurate data, even if limited in scope or completeness, can be successfully used to deliver analytic insight. Clearly, however, the more complete the data the more robust the analytic models are likely to be. Similarly, customer-centric data is going to provide more opportunities for more interesting analytics than account-level data. Thus projects to improve master data management and customer data integration will materially improve the quality of models being developed as well as offering new opportunities for models. Organizations should consider these kinds of projects in parallel with the development of EDM.

Projects to improve data quality and completeness are synergistic with EDM projects. By focusing data integration and quality effort on projects where analytics are being developed it is possible to apply resources more effectively. Knowing what kind of insight is being sought can help prevent wasted effort by focusing on those areas where more or better data will drive better business results.

Constantly evaluating the data that might help make a decision more effectively should become part of the company culture. This might result in projects to enhance data capture, to capture new information about customers or products say, or attempts to find data outside the organization. Some organizations are sophisticated consumers of external data, such as geographic data, consumer data or demographic/census data. Others are not. This kind of external data, if it can be integrated with internal records and applied to specific problems, can add a lot of value to analytic models being developed. As EDM projects progress teams should constantly ask if there is external data that can be applied to improve the quality of insight or to derive new insight. While privacy issues are real and must be properly considered, external data can enrich analytic models very significantly.

Technorati Tags: analytics, data mining, data warehouse, decision automation, innovation, readiness, data

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How do you tell if your organization is ready for decision management? If not, what can you do to start laying the groundwork?

While there are many characteristics of an organization that might identify it as a good, or a poor, candidate for decision management, none of them prevent progress being made completely. Each organization needs to understand the different areas of readiness and decide how to leverage those things it does well and mitigate those things it does poorly. The five key areas are business and IT collaboration, data readiness, analytic understanding, willingness to change (both in terms of internal processes and customer-facing ones) and management focus on operations. In five posts this week I will try and cover each of them.

First, Business and IT collaboration

Automated operational decisions are perhaps the point in an application portfolio where information technology and the business came together most closely. Business decisions are, by their nature, intensely important to the business and to the customer-facing management. These decisions are often regulated in ways only certain business people understand, must conform to policies written by the business and must take account of fluctuations in the market - small and large, long-term and rapid. Insight from data, another key ingredient in decision services, is also highly dependent on the business context. No predictive model is worth anything if it does not predict something of interest to the business, at a level of accuracy useful to the business, early enough for some business response. Yet decision services must also manipulate corporate data, integrate with high volume systems and be on the critical path for customer-facing applications. IT departments have invested a great deal of time and money in making sure their applications meet performance and scalability requirements, privacy rules and so on. To build effective decision services, then, requires the business and IT to collaborate as never before.

While technologies for decision management can be selected, in part, to address these issues of collaboration, there is a still a cultural aspect to this issue. Some IT departments are simply not trusted by some business units and some IT departments return this suspicion. Part of any plan to move to Decision Management must be the resolution of these kinds of issues. This will require proof points - no amount of talking and promising will typically do as most organizations have too many issues with information systems in their recent past. Establishing trust and mutual respect by delivering a series of decision services that work and that can be controlled by the business and then having them not break the systems that IT manages when the business changes them is key.

One possible approach here is to pair business analysts and programmers (similar to pair programming approaches) and have them work on the same problem. With a rules-based approach that allows both to understand the core logic being "coded" this can work very effectively. Even if you don't go this far, it will be important to keep the business analysts and users engaged in the design process as it is easy for IT folks to design something which cannot be maintained by a business user, even if that was the intent. The way a programmer looks at a problem is often very different from how a business user or analyst will look at it. Designing for business user control of the decision service will only work if the business users understand how the service works and can map their understanding of the business to the design of the service in a way that let's them apply their business knowledge.

Some previous posts worth checking out on this topic:

Technorati Tags: BRMS, business agility, business rules, collaboration, decision automation, readiness

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Boomers Who Can Afford Home Monitoring Systems May Remain at Home Longer — In the future, sensor technology could provide limitless opportunities for preserving the independent lifestyles of the Baby Boomer generation while preventing illness and injury. Wearable sensor networks embedded in clothing, for example, could monitor a person's gait for irregularity, and address the abnormality prior to a potentially painful fall. Some clothing sensors could also notify a caregiver if the wearer falls or experiences another medical problem, prompting an automatic call for help.

While there is clearly a need for new sensor and monitoring technologies in this scenario,it also shows the need for decision automation. All these sensors will have limited intelligence embedded. The ability to tell the difference between a change in routine and a crisis might well involve interpreting signals from multiple sensors. Different doctors will want to monitor different patients in different ways to reflect the unique circumstances of each. Inferring the right moment to tell a medical provider about a specific patient requires a complex decision that will need to be automated. The combination of business rules (so that patients, medical equipment providers and doctors can all participate in setting the rules) and powerful analytics that predict approaching problems from data being gathered is ideal for this kind of automation. Indeed there is at least one example of monitoring heart patients on my other blog and clearly things like diabetes are getting close to this approach already.

Technorati Tags: analytics, business rules, medical device, predictive analytics, remote monitoring

Posted by jtaylor in Business Rules • Decision Technologies • Innovation • Predictive Analytics | Permalink | Comments (0) | TrackBacks (0)

I am attending webMethods Integration World this week and blogging live from the sessions. Day 2 had the customer innovation awards. These will be listed on the webMethods site I am sure (with videos) and were fascinating.

• The first one was Johnson and Johnson Health Care talking about how their supply chain has gone from low urgency (shipping to warehouses) to an increasingly just-in-time deliver of medical supplies to doctors for procedures. Use webMethods to measure end to end supply chain, monitor it and respond quickly to problems and issues. Indeed able to be proactive fixing problems with deliveries before customers notice and to increase awareness and understanding of all their supply chain related processes.
• The second one was Genentech. Integrating applications to make it easy to support rapidly expanding businesses while still reusing compliant pieces so as to avoid having to re-start approval from the FDA etc. SOA, standardization and simplification were crucial to establish expansion to be supported by IT. Focused on reusable code and have had some success with developing core services and getting high levels of reuse. Adaptability has been improved by building a flexible architecture which they see as important given how constant change was and is. Decoupled manufacutring, new product introduction etc from IT needs. Want to move dollars from IT to research.
• The third one was Ahold, about whom I blogged yesterday. Great comment that when you start with innovation and change you don't have many friends but when you succeed, you have many!

I am speaking at 2:45pm on "Automating High-Volume Business Decisions within an SOA"

Technorati Tags: business process management, CRM, innovation, legacy modernization, service, SOA, supply chain, webMethods

Posted by jtaylor in Business Process Management • Innovation • Legacy Modernization • SOA | Permalink | Comments (0) | TrackBacks (0)

I am attending webMethods Integration World this week and blogging live from the sessions. Day 2 moved on with Bruce Richardson of AMR talking about the future of Enterprise Software. Will it be SOA vs Packaged Applications?

Bruce thinks that the future of software does not include the concept of a large, packaged applications. Bruce feels that three things are coming together - SOA (which he is starting to believe is here to say), web 2.0 (enriching the user experience), model-driven development (like Workday, Dave Duffield's new company). His surveys suggest that the state of software innovation is accelerating and the line of business is more optimistic. They see more innovation in the future and so are looking for new technology drive new levels of agility and productivity.

His premise is that collaboration and business process/SOA approaches are going to replace basic connectivity and an ERP-centric backbone. He talks about a "pig in the python" where there is a huge digestion issue with all the new future ERP architectures. Customers can see the future but cannot get by the time/cost of upgrades, no down-time for changes, lack of detailed roadmaps and a lack of business architects. The future potential for innovation is being obstructed by this and the time to innovate for the ERP vendors. Meanwhile 70% of survey respondents think that SOA is crucial to future innovation, especially in reducing the cost of IT and the cost of delivering new IT. The need to get at, and work down, the IT backlog is a big deal and SOA helps enable this. I think that rules do also and have blogged about this before in terms of your value backlog.

Bruce is very optimistic about how SOA and other trends are going to drive more software innovation in the next few years than ever before. He thinks that the SOA and BPM/composite applications approach will replace the large enterprise application. I think that the need for decision automation as part of making services have intra-service agility, as part of making a web 2.0 interface truly support self-service and to make declarative, business-user centric development a reality!

I am speaking at 2:45pm on "Automating High-Volume Business Decisions within an SOA"

Technorati Tags: business agility, business rule, business rules, composite application, CRM, decision automation, innovation, service, SOA, webMethods, AMR

Posted by jtaylor in Business Agility • Business Rules • Decision Technologies • Innovation • SOA | Permalink | Comments (0) | TrackBacks (0)

I am attending webMethods Integration World this week and blogging live from the sessions. Day 2 began with a keynote from John Hagel (who has a fun blog here) on "Loosely Coupled Business Architecture"

John had no slides (delightful) and discussed what he sees as an opportunity to move to a different approach to business process management. There is according to John a tendency of companies to focus on tight coupling of business processes where, perhaps, there is more opportunity in loose coupling of processes. He used a couple of examples on this:

• Lee and Fung manufacturers customized product and supply chains for clothes designers. Designs come in, they set up the production network. Very time and cost sensitive environment and complex as physical goods must be moved across national boundaries. They have some 10,000 business partners in 48 countries and focus on managing them and quality control. They developed tailored networks for customers and for specific product lines for each customer. Very flexible and dynamic.
  While Western companies are trying to reduce the number of participants in their supply chain for efficiency, Lee and Fung manages theirs by taking a very component focused approach to business process management. They design "components" with defined interfaces, measures etc. These can then be packaged rapidly with other components and so used to develop complex, custom processes. This approach prevents the problem of increasingly low returns from adding partners (caused by increased complexity).
• Motorcycle manufacturers in China (did not catch the names) competed with the big Japanese motorcycle vendors not by trying to create a better, tightly coupled product environment. They broke the design into pieces, relaxed the detail in the design (rough sketches only) but very strict about the design requirements and performance/reliability issues. They also told the partners to figure out the interdependencies themselves - they did not even define the "interfaces" between the components. This approach drove very deep specialization and some intense "friction" between the design companies (with the aggressive performance targets). This approach has driven the price of a motorcycle from $700 to $200 and now China makes 50% of the worldwide motorcycle market.
• Original design manufacturers (ODMs) in Taiwan also use this approach to develop electronics. Even things like an iPod have an ODM as a key partner. John did not go into much detail other than to say that this is how they develop a wide range of products with intense flexibility .

SOA is, he says, perhaps the first approach that supports this kind of loosely coupled design/process management philosophy because SOA too is loosely coupled. Although there is a short term benefit from SOA around leveraging existing resources and reduce existing complexity he feels that the long term benefit comes from enabling this kind of company-level loose coupling. John regards this as a long term competitive advantage that will allow companies to develop the flexibility they need to compete in a global economy. Great presentation and as I have said before I think control over the key decision points in a process, in a loosely coupled and reusable way, is going to be crucial and this is the core concept of decision management.

His book is "The only sustainable edge" with John Seely Brown

I am speaking at 2:45pm on "Automating High-Volume Business Decisions within an SOA"

Technorati Tags: business agility, business process management, composite application, service, SOA, webMethods

Posted by jtaylor in Business Agility • Business Process Management • Innovation • SOA | Permalink | Comments (0) | TrackBacks (0)

I am attending the Delphi Business and Process Innovation Summit this week and blogging as I go. Next up was David Eckoff on "Innovation at the intersection of media and technology". This was a fairly humorous session for various reasons, not least that it was the end of the day and so everyone was a little punchy.

Media industry used to have very limited choices in terms of TV channels, movies only at movie theaters etc. Very homogeneous but not any more. Now many more kinds of channels, time-shifting with TIVO-like devices, place-shifting with Slingbox and so on. Fragmentation and choice are king and disruptive innovation is now a way of life in the media industry. Consumers are now creating content too - at concerts for example, people post photos, commentary etc. Lots of new deals and gadgets make for constant churn. Turner, David's employer, is trying to innovate in this environment. For example the new site, veryfunnyads.com, a place to see funny ads and email it around to people. Very consumer-driven, very viral. He showed a couple and some were very funny (like the March of the Penguins one from France). They make money from advertising around the advertising :-). Similarly a PPV service for minority sports PlayOn used by the Atlantic Conference for college sports. Key innovation by Turner was to provide a production kit (based on CNN field crews) for producing these TV shows cheaply and easily. Each school has one, they have interns working this! Completely handed over to rights holder so they can produce it themselves.

10 lessons learned about innovation at Turner:

• Innovate when you have a healthy core - as have money, opportunity for focus etc.
• Perfection is the enemy of innovation - good enough where it has to be, better where it can be
• Traditional metrics aren't helpful for analysis of markets that don't yet exist - very true!
• Innovation is a process
• Different resources and approaches for defending the castle vs exploring new territory
• Be seen as an ally - relationships matter
• Get some early wins
• Rome wasn't built in a day
• If you want to beat Bobby Fisher, don't play chess! - don't tackle big enemies in their area of strength
• Survival of the most adaptable

There was a lot of discussion about blogging so "hello" to everyone from the session! David's blog is www.davideckoff.com. That's it for today, I am speaking tomorrow.

Technorati Tags: innovation

Posted by jtaylor in Innovation | Permalink | Comments (0) | TrackBacks (0)