Interview with James Taylor, Author of "Smart (Enough) Systems"
0 Comments Published by John Dillard on Monday, July 30, 2007 at 10:29 AM.
James Taylor, a frequent commenter on this blog and the author of one of the best decision analytics blogs out there, recently published a guide to Enterprise Decision Management called Smart (Enough) Systems. We recently had the chance to speak to James about the book and about the relationship between technology and effective decision-making.
BST: Thank you for taking the time to talk to us about your new book, Smart (Enough) Systems. What motivated you to write a book on this subject?
JT: It seemed to me that there was a very limited awareness of how existing technologies were being used to make point systems smarter – both in terms of companies who had used the technology in one area but not others and in terms of companies who did not seem to realize what was possible. Companies were putting up with really “dumb” systems because they thought the alternative was something that only existed in the lab. Neil’s experience was very similar in that he too saw companies getting far too little value out of their data. A book offers both a platform for explaining something thoroughly and a “proof point” that this is a serious and “real” approach.
BST: You place a lot of emphasis on Operational Decisions in the book. Could you talk about why they are particularly important?
JT: It is not so much that operational decisions are more or less important than, say, strategic decisions. It is more that they are totally neglected in most organizations. When I talk to companies about their operations and identify the decisions that drive the high volume systems and processes in their business, they have typically not even considered them. The operational decisions that make or break the profitability of a customer or the cost of a transaction are delegated to programmers, front-line staff or generic software packages almost without thought. That’s why the book focuses so much on them – they are sadly neglected.
BST: We found your discussion of strategic alignment and choosing the right decisions particularly important in the book. How critical is it for organizations to find the right decisions to improve?
JT: Well the approach we outline in the book is clearly aimed at a certain class of decisions, operational decisions as you note, and so focusing on that kind of decision is very important. It won’t work well to try and use enterprise decision management, the approach outlined in the book, to manage and improve strategic decisions for instance. That said I think companies can use the techniques and technologies we discuss on a very wide range of decisions and that it is not critical to pick the right one out of them to get started. One of the hardest problems can be getting people to realize that decisions are being made in a certain point in a process and then getting them to focus on it as a distinct opportunity for improvement. Given this difficulty it may well be that you have to start with the decisions people can “see”.
BST: We have written about how many organizations that could be applying more sophisticated decision analytics – or any type of more rigorous quantitative analysis – haven’t yet done so. How do you convince these more reluctant organizations that there is real value in this approach?
JT: Well I think the biggest issue is understanding how they can apply these things to their operations and the focus on decisions, not on reports or analysis, is critical. I think the process we lay out in the book that takes a series of baby steps to get more and more sophisticated about decision-making having called out and focused on the decision.
BST: The book emphasizes the importance of business rules, and of having an integrated development environment to hold those rules to provide services. This is a very similar concept to Identity Management, which provides a central database to manage the user lifecycle across multiple connected systems based on business rules and policies. Given the similarity of these approaches, do you see a convergence of these technologies, and if so, what do you see as the end game?
JT: That’s an interesting question and one I have not really thought about. In general, I tend to differentiate between using rules as part of solving a problem (like identity management) and focusing explicitly on decisions and decision management, using rules. In this case, then, I would expect to see rules-based identity management (using rules to make identity management decisions) and a separate use of rules as part of taking control of business decision making.
BST: In several examples in the book, you discuss not only the technical challenges to EDM, but also the cultural challenges. What are the most common cultural barriers/challenges that organizations must overcome to adopt better decision making methodologies? Are these challenges restricted to “traditional” businesses (like banking)?
JT: I think there are a number. There is a lack of management focus on operations – execs see their role as making strategic decisions not improving execution. There is a lack of trust and collaboration between IT and business units that make collaborating on decision management hard. Data is often poorly understood and what understanding there is tends to be backward facing not forward. Lastly there is a change issue – can companies really change the way they regard operational decisions. Each varies in companies but all are an issue that need to be considered as part of an adoption plan.
BST: Another interesting point you make is the need to enable IT capabilities so that IT can be where the business needs it. This can be a bit of a chicken and egg problem, because in many organizations the IT department is seen as a cost center and as such, it is often starved for funds. Who typically drives these infrastructure changes? In your experience, are there particular governance models that enable the type of adaptability and collaboration necessary to make EDM efforts successful?
JT: Well there are a couple of perspectives. A risk-based approach where the risk of not being able to change systems drives a willingness to invest in modernization (calculate the risk to the company of not being able to change systems quickly enough or where their accuracy is too poor). An opportunity-based one where the approach is applied only to new systems and the more effective development and ongoing evolution of those applications gradually frees up dollars to revisit old ones. Lastly there is a growth-oriented one where a company allows a proposal to spend money for a return that drives a new decision automation project that drives additional revenue. The additional revenue is then allocated to clean up old ones. There’s no magic bullet.
BST: If your readers want to learn more about this discipline, what would you recommend that they read next (after they read “Smart Enough Systems”)?
After they read it and recommend it to all their friends you mean? Well, there are some good blogs out there (yours, mine and others) on analytics (both technical and organizationally focused), rules, and customer-experience. There are some great books too – Competing on Analytics, Linnoff and Berry on Data Mining, The Business Rules Revolution and many others – on the specifics of various parts of the approach (all of these are listed on the companion site, www.smartenoughsystems.com) . Mostly, though, I would suggest starting! The hardest thing is having experience so getting started is key.
BST: Thank you for taking the time to talk to us about your new book, Smart (Enough) Systems. What motivated you to write a book on this subject?
JT: It seemed to me that there was a very limited awareness of how existing technologies were being used to make point systems smarter – both in terms of companies who had used the technology in one area but not others and in terms of companies who did not seem to realize what was possible. Companies were putting up with really “dumb” systems because they thought the alternative was something that only existed in the lab. Neil’s experience was very similar in that he too saw companies getting far too little value out of their data. A book offers both a platform for explaining something thoroughly and a “proof point” that this is a serious and “real” approach.
BST: You place a lot of emphasis on Operational Decisions in the book. Could you talk about why they are particularly important?
JT: It is not so much that operational decisions are more or less important than, say, strategic decisions. It is more that they are totally neglected in most organizations. When I talk to companies about their operations and identify the decisions that drive the high volume systems and processes in their business, they have typically not even considered them. The operational decisions that make or break the profitability of a customer or the cost of a transaction are delegated to programmers, front-line staff or generic software packages almost without thought. That’s why the book focuses so much on them – they are sadly neglected.
BST: We found your discussion of strategic alignment and choosing the right decisions particularly important in the book. How critical is it for organizations to find the right decisions to improve?
JT: Well the approach we outline in the book is clearly aimed at a certain class of decisions, operational decisions as you note, and so focusing on that kind of decision is very important. It won’t work well to try and use enterprise decision management, the approach outlined in the book, to manage and improve strategic decisions for instance. That said I think companies can use the techniques and technologies we discuss on a very wide range of decisions and that it is not critical to pick the right one out of them to get started. One of the hardest problems can be getting people to realize that decisions are being made in a certain point in a process and then getting them to focus on it as a distinct opportunity for improvement. Given this difficulty it may well be that you have to start with the decisions people can “see”.
BST: We have written about how many organizations that could be applying more sophisticated decision analytics – or any type of more rigorous quantitative analysis – haven’t yet done so. How do you convince these more reluctant organizations that there is real value in this approach?
JT: Well I think the biggest issue is understanding how they can apply these things to their operations and the focus on decisions, not on reports or analysis, is critical. I think the process we lay out in the book that takes a series of baby steps to get more and more sophisticated about decision-making having called out and focused on the decision.
BST: The book emphasizes the importance of business rules, and of having an integrated development environment to hold those rules to provide services. This is a very similar concept to Identity Management, which provides a central database to manage the user lifecycle across multiple connected systems based on business rules and policies. Given the similarity of these approaches, do you see a convergence of these technologies, and if so, what do you see as the end game?
JT: That’s an interesting question and one I have not really thought about. In general, I tend to differentiate between using rules as part of solving a problem (like identity management) and focusing explicitly on decisions and decision management, using rules. In this case, then, I would expect to see rules-based identity management (using rules to make identity management decisions) and a separate use of rules as part of taking control of business decision making.
BST: In several examples in the book, you discuss not only the technical challenges to EDM, but also the cultural challenges. What are the most common cultural barriers/challenges that organizations must overcome to adopt better decision making methodologies? Are these challenges restricted to “traditional” businesses (like banking)?
JT: I think there are a number. There is a lack of management focus on operations – execs see their role as making strategic decisions not improving execution. There is a lack of trust and collaboration between IT and business units that make collaborating on decision management hard. Data is often poorly understood and what understanding there is tends to be backward facing not forward. Lastly there is a change issue – can companies really change the way they regard operational decisions. Each varies in companies but all are an issue that need to be considered as part of an adoption plan.
BST: Another interesting point you make is the need to enable IT capabilities so that IT can be where the business needs it. This can be a bit of a chicken and egg problem, because in many organizations the IT department is seen as a cost center and as such, it is often starved for funds. Who typically drives these infrastructure changes? In your experience, are there particular governance models that enable the type of adaptability and collaboration necessary to make EDM efforts successful?
JT: Well there are a couple of perspectives. A risk-based approach where the risk of not being able to change systems drives a willingness to invest in modernization (calculate the risk to the company of not being able to change systems quickly enough or where their accuracy is too poor). An opportunity-based one where the approach is applied only to new systems and the more effective development and ongoing evolution of those applications gradually frees up dollars to revisit old ones. Lastly there is a growth-oriented one where a company allows a proposal to spend money for a return that drives a new decision automation project that drives additional revenue. The additional revenue is then allocated to clean up old ones. There’s no magic bullet.
BST: If your readers want to learn more about this discipline, what would you recommend that they read next (after they read “Smart Enough Systems”)?
After they read it and recommend it to all their friends you mean? Well, there are some good blogs out there (yours, mine and others) on analytics (both technical and organizationally focused), rules, and customer-experience. There are some great books too – Competing on Analytics, Linnoff and Berry on Data Mining, The Business Rules Revolution and many others – on the specifics of various parts of the approach (all of these are listed on the companion site, www.smartenoughsystems.com) . Mostly, though, I would suggest starting! The hardest thing is having experience so getting started is key.
Why Optimizing Decisions is the Most Important Thing You Can Do, Part III
1 Comments Published by John Dillard on Monday, July 09, 2007 at 12:36 PM.
In our last post in this series, we introduced a simple, four-step approach to optimize decisions that we call Decision-Centric Business Improvement. The critical decisions identified through that four-step process represent the resource-intensive turning points of every organization’s growth. These decisions are diverse; some are large: corporate acquisitions, multi-billion dollar procurements, and 5-year strategic goals. Some are smaller: choosing a commodity supplier, making a hiring decision, or choosing the functionality of a software solution. Some decisions are manual, while some are automated. Some require one person; some require groups or even multiple organizations.
The last step in Decision-Centric Business Improvement is optimizing decisions along three angles: strategic relevance, technique, and technology. When optimizing decisions, it is critical that an organization work through each of these angles to build a coherent, balanced approach to the decision in question. The figure below illustrates these three “angles” of decision making.
The Decision Strategy Angle
The first angle of effective decision making is how the decision influences advancement of the organizational strategy. To clearly understand this angle, an organization should isolate the most important strategic metrics of the organization and describe the decision in terms of those metrics. If a decision cannot be shown to have a measurable impact on strategic goals, there is little chance that the decision can be successful.
The right approach in this angle is not to develop a new strategy, but rather to understand the strategy (whether implicit or explicit) and to define a particular decision in the context of the strategy. Traditional strategic planning tools—such as SWOT analysis, multiple forces analysis, or Value Chain Analysis—may be useful in this angle but should be focused on the decision.
The Decision Technique Angle
The second angle of effective decision making is the selection and application of the right tool for the job. A carpenter wouldn’t use a sledgehammer to drive carpet tack; similarly, a good decision maker chooses the tool that is just complex enough—but no more complex—to do the job. In this angle, an organization must understand both the soft and hard aspects of the decision. Hard aspects include the required speed and frequency of a decision, as well as the number of variables involved and whether the decision requires descriptive (backward-looking) or predictive (forward-looking) results. Soft aspects invlude the level of organizational buy-in required, political consequences, human factors, and transparency requirements.
For an automated supply chain decision, an organization might choose to develop a sophisticated algorithm that completes on the fly multivariate analysis. For a one-time strategic decision at a board meeting, it might use a decision tree or a consensus building method. Hypothesis testing, analytic network process, analytic hierarchy process, real options are other approaches that might be used to aid decision making.
The Decision Technology Angle
The third angle of effective decision making is the application of appropriate technology to enable the decision. Most organizational decisions will benefit from better management and distribution of information aided by technology, but not all. Knowing if, when, and how to apply technology is the component of decision optimization least understood and most prone to error.
Good decisions result from a qualified decision maker armed with the right information, delivered at the right time in the right context.
Rather than selecting one-off technology solutions, an organization should understand their “Decision Architecture” – an architecture optimized for effective decision-making. In many cases, this architecture may be comprised of existing systems rather than expensive new ones. Effective organization and adaptation of organizational IT can transform decision-making capabilities in many organizations.
While “hard” decisions—those with many variables or high speed requirements—are the most obvious candidates for the application of technology, technology can be a critical enabler of softer decisions too. Collaboration tools, role-based access control, and innovative application of existing technology (like wikis) can be critical enablers of infrequent, collaborative decision-making. In every analysis of a critical decision, whether “hard” or “soft,” technology should be considered as a important enabler of long-term success.
The last step in Decision-Centric Business Improvement is optimizing decisions along three angles: strategic relevance, technique, and technology. When optimizing decisions, it is critical that an organization work through each of these angles to build a coherent, balanced approach to the decision in question. The figure below illustrates these three “angles” of decision making.
The Decision Strategy Angle
The first angle of effective decision making is how the decision influences advancement of the organizational strategy. To clearly understand this angle, an organization should isolate the most important strategic metrics of the organization and describe the decision in terms of those metrics. If a decision cannot be shown to have a measurable impact on strategic goals, there is little chance that the decision can be successful.
The right approach in this angle is not to develop a new strategy, but rather to understand the strategy (whether implicit or explicit) and to define a particular decision in the context of the strategy. Traditional strategic planning tools—such as SWOT analysis, multiple forces analysis, or Value Chain Analysis—may be useful in this angle but should be focused on the decision.
The Decision Technique Angle
The second angle of effective decision making is the selection and application of the right tool for the job. A carpenter wouldn’t use a sledgehammer to drive carpet tack; similarly, a good decision maker chooses the tool that is just complex enough—but no more complex—to do the job. In this angle, an organization must understand both the soft and hard aspects of the decision. Hard aspects include the required speed and frequency of a decision, as well as the number of variables involved and whether the decision requires descriptive (backward-looking) or predictive (forward-looking) results. Soft aspects invlude the level of organizational buy-in required, political consequences, human factors, and transparency requirements.
For an automated supply chain decision, an organization might choose to develop a sophisticated algorithm that completes on the fly multivariate analysis. For a one-time strategic decision at a board meeting, it might use a decision tree or a consensus building method. Hypothesis testing, analytic network process, analytic hierarchy process, real options are other approaches that might be used to aid decision making.
The Decision Technology Angle
The third angle of effective decision making is the application of appropriate technology to enable the decision. Most organizational decisions will benefit from better management and distribution of information aided by technology, but not all. Knowing if, when, and how to apply technology is the component of decision optimization least understood and most prone to error.
Good decisions result from a qualified decision maker armed with the right information, delivered at the right time in the right context.
Rather than selecting one-off technology solutions, an organization should understand their “Decision Architecture” – an architecture optimized for effective decision-making. In many cases, this architecture may be comprised of existing systems rather than expensive new ones. Effective organization and adaptation of organizational IT can transform decision-making capabilities in many organizations.
While “hard” decisions—those with many variables or high speed requirements—are the most obvious candidates for the application of technology, technology can be a critical enabler of softer decisions too. Collaboration tools, role-based access control, and innovative application of existing technology (like wikis) can be critical enablers of infrequent, collaborative decision-making. In every analysis of a critical decision, whether “hard” or “soft,” technology should be considered as a important enabler of long-term success.
Labels: automation, business process, decision optimization, Decision-Centric Business Improvement, decisions, Identity Management, IT, triangle
