Why optimizing decisions is the most important thing you can do
4 Comments Published by John Dillard on Saturday, February 17, 2007 at 5:38 PM.
The most important piece of advice we can give to organizations and their leadership for the next 30 years is this:
Optimizing decisions is the single most important factor in long-term organizational success. It's more important than strategy, organization design, quality, customer relationship management, innovation, or any other business model, technique, or practice.
That statement is provocative, but it's the reason why we started a company. It also begs the question, "What has changed to make optimized decisions so important?" This post outlines some of the reasons why; the next post will discuss ideas on what to do about it. The reasons are far too many to list here, but below are my views of the key interdependent factors.
1) Business model innovation. Innovations in business models--the underlying mechanisms that define the way organizations operate to provide goods and services--have been changing at breakneck speed in the last 15 years, and there is no reason to expect a coming period of stabilization. Organizations that are successful don't adopt a model and stick with it; they are hyper-adaptive to new business model opportunities when they emerge. The number of choices in business models and the resulting consequences are rapidly multiplying.
2) Intensifying expectations for regulatory compliance. Companies and governments entered a new era after 9/11 and the Enron scandal marked by a dramatic intensification of oversight by shareholders, regulatory authorities, Congress, OMB, and others. Not only is there pressure to make critical decisions quickly and accurately, but organizations must explain to overseers why the decisions were made. This new emphasis on transparency of decision-making is not supported by 20th century decision-making processes.
3) Compressing decision cycles. As business models shift and information becomes more accessible and available, organizations are faced with compressing decision cycles, particularly in critical capability processes. They have less time to choose options, and more options to choose from. In any decision, data must be aggregated, criteria established, options considered, and decisions made. Organizations have less and less time to pass each gate.
4) Advancing decision automation. Advancements in artificial intelligence compound the severity of the decision making problem. More and more decisions may be automated every year, placing additional pressure on manual decisions to either be expedited or automated themselves. Critical decisions will either be severe time traps in critical processes, or the source of substantial competitive advantage. Ignore this technology at your peril--over the next ten years the ability of software to solve complex, unstructured problems will revolutionize what organizations define as their core capabilities. James Taylor writes the best blog out there on decision automation.
5) Accelerating acceleration. As everyone knows, the innovation in technology, business, and life is accelerating. This is well documented---Moore's Law and studies of technology adoption curves are just two good pieces of evidence. However, what places so much more pressure on decision cycles is that the rate of change is also accelerating. Why? Because enablers of innovation are themselves undergoing rapid, logarithmic change. Ray Kurzweil and Alvin and Heidi Toffler have done some great writing on this phenomenon.
These are just five thoughts on my list. . . it's certainly not exhaustive. Our next post will focus on how we view solutions to the challenge--specifically, decision-centric capability development.
Optimizing decisions is the single most important factor in long-term organizational success. It's more important than strategy, organization design, quality, customer relationship management, innovation, or any other business model, technique, or practice.
That statement is provocative, but it's the reason why we started a company. It also begs the question, "What has changed to make optimized decisions so important?" This post outlines some of the reasons why; the next post will discuss ideas on what to do about it. The reasons are far too many to list here, but below are my views of the key interdependent factors.
1) Business model innovation. Innovations in business models--the underlying mechanisms that define the way organizations operate to provide goods and services--have been changing at breakneck speed in the last 15 years, and there is no reason to expect a coming period of stabilization. Organizations that are successful don't adopt a model and stick with it; they are hyper-adaptive to new business model opportunities when they emerge. The number of choices in business models and the resulting consequences are rapidly multiplying.
2) Intensifying expectations for regulatory compliance. Companies and governments entered a new era after 9/11 and the Enron scandal marked by a dramatic intensification of oversight by shareholders, regulatory authorities, Congress, OMB, and others. Not only is there pressure to make critical decisions quickly and accurately, but organizations must explain to overseers why the decisions were made. This new emphasis on transparency of decision-making is not supported by 20th century decision-making processes.
3) Compressing decision cycles. As business models shift and information becomes more accessible and available, organizations are faced with compressing decision cycles, particularly in critical capability processes. They have less time to choose options, and more options to choose from. In any decision, data must be aggregated, criteria established, options considered, and decisions made. Organizations have less and less time to pass each gate.
4) Advancing decision automation. Advancements in artificial intelligence compound the severity of the decision making problem. More and more decisions may be automated every year, placing additional pressure on manual decisions to either be expedited or automated themselves. Critical decisions will either be severe time traps in critical processes, or the source of substantial competitive advantage. Ignore this technology at your peril--over the next ten years the ability of software to solve complex, unstructured problems will revolutionize what organizations define as their core capabilities. James Taylor writes the best blog out there on decision automation.
5) Accelerating acceleration. As everyone knows, the innovation in technology, business, and life is accelerating. This is well documented---Moore's Law and studies of technology adoption curves are just two good pieces of evidence. However, what places so much more pressure on decision cycles is that the rate of change is also accelerating. Why? Because enablers of innovation are themselves undergoing rapid, logarithmic change. Ray Kurzweil and Alvin and Heidi Toffler have done some great writing on this phenomenon.
These are just five thoughts on my list. . . it's certainly not exhaustive. Our next post will focus on how we view solutions to the challenge--specifically, decision-centric capability development.
Labels: artificial intelligence, automation, decision optimization, decisions
Nice post. So nice that I am going to blog about it.
JT
www.edmblog.com
... and not just because you like my blog.
Hi John - this is an interesting post and you articulate ideas that stirred up thoughts in my own head. The questions that come up for me are in the area of what kind of decisions do you advocate automating and how do you advocate actually automating them.
I'm interested to hear what are the characteristics of decisions you believe to be best handled through automation. You make reference to complicated and unstructured decisions being automated. Are these the best decisions to automate?
I'm interested to hear about the technology used to automate such decisions. How does it work? what does it cost? What companies are currently using it for what kind of applications?
Also I associate the phrase "Big Sky" with the fine state of Montana, is that where you are located?
Michael,
Great questions. Here is my take:
On automating complicated an unstructured decisions, I would say that technology can definitely help apply structure to what seems unstructured. I am no expert on this, but more advanced data mining techniques have had great success is "filling" holes in unstructured data to make it more usable. As for suitability of these decisions for automation, I think we will see automation move into previously inconceivable areas that are more predictive and more capable of simulating, but not replacing, human judgment. Ask again in 10 years and the answer to that will be radically different--or if you really want your noodle cooked, go check out the AI articles on www.kurzweilai.net.
As for the technology and how it works, I would point you to www.edmblog.com because it's going to give you a far better answer than I can. However, I will say that the confluence of data mining, identity management, and predictive analytics are some of the components of the technology. It's pretty widely used in insurance (think risk profiling), banking, and the credit industry (a credit score is really a form of decision automation), and in marketing (see http://marketingroi.wordpress.com/) for more on marketing applications.
Cost is sticky; I don't think there is one answer. I am working on something with a client right now that uses a simple screening tool applied to a set of criteria that we will identify using discriminant analysis. It will be cheap (less than $50k). That said, I could easily see implementations in some industries in that involve substantial re-architecting, which would of course spin well in to the millions upon millions.
About our name: truth be told, we are not in Big Sky; we are in Atlanta and Washington, DC. There is a Montana story involved, however. . perhaps we'll post the story of the name soon.
Thanks for the comment!
John
Michael,
I wanted to follow up on John's response with an example where clients are using technology to help them automate decisions based on currently unstructured data stored in different systems. If we take a look at the Identity Management space, which really falls under the aegis of Master Data Management, we find that one of the greatest obstacles to enterprise decision automation / decision management is the inability to effectively manage authorization data for users. In other words, the ability to automatically decide who has permission to do what. Today, authorization management is largely localized at the application level, and it’s costly and prone to error. System administrators typically control user access through the creation and maintenance of access control lists (ACLs) for each resource (e.g. application, server). And for a company with 50,000 users and 500 applications, this becomes the Gordian Knot of enterprise computing. Implementing automated permissions helps organizations make the leap from making one-off decisions to automating the enterprise decision-making process.
This leap forward is accomplished through Roles Based Access Control (RBAC), which offers a more efficient and effective tool for automatically granting users access to the applications and systems that they need to be productive. The definition of roles allows authorization data to be managed at a higher-level, assigning users to roles and then managing the association of a group of users with a role. This may sound straightforward, but it requires companies to create a system that automatically manages users’ authorizations based on a matrix comprised of the user’s job titles/roles, role hierarchies, security policies, and business rules. Until recently, there have been few tools to help companies tackle this issue, leaving the promise of RBAC largely unfulfilled.
While defining roles can be a real nightmare, there are some new tools available that can help companies organize this unstructured data across applications and systems, to come up with a solution that automates decisions about who should have access to what and when.
The tools that support RBAC are relatively new, however, there are three companies that we know of that provide tools to address this problem:
Bhold (http://www.bholdcompany.com/ ),
Bridgestream SmartRoles (http://www.bridgestream.com ), and
Eurekify Sage ( http://www.eurekify.com/ ).
These tools offer organizations improved efficiency, security, and reliability by aggregating and structuring seemingly unrelated and widely distributed authorization data from application and system access control mechanisms [and other RBAC data like job titles and business rules] into an enterprise-level authorization solution.
I think this example ties in nicely to John’s framework where organizations are freeing up resources (people and money) to focus on innovation instead of administration. Regulatory compliance (e.g. Sarbanes-Oxley among others) becomes much easier with a centralized system that applies policies uniformly across multiple applications, etc.