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Importance of decisions OMG

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A presentation on decisions and decision management to the OMG standards group discussing a Decision Model Notation.

A presentation on decisions and decision management to the OMG standards group discussing a Decision Model Notation.

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  • When you are thinking about repeatable processes and decisions it is important to consider them both. For day to day operations, process and decision definitions are equally essential - normative - while also being very descriptive.
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  • James,
    What about process? What is normative and what is descriptive?
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  • Large companies rely on their Enterprise Resource Planning (ERP) and other supply chain systems to manufacture, distribute and manage the products their customers need. The behavior of these operational systems is critical to how a company treats, and is perceived by, its customers, its partners and its suppliers. Yet these systems are often plagued by manual interventions that delay processes, by hard to change constraints and thresholds and by problems with local exceptions to global processes. This session will show how using Decision Management to apply business rules and analytic technology can upgrade your ERP to be smarter and more agile. Illustrated with case studies, one attendee will receive a free signed copy "Applying Real-World BPM in an SAP Environment".
  • At its heart a decision is a choice, a selection of a course of action. A decision is arrived at after consideration and it ends uncertainty or dispute about something.Decisions are made only after considering various facts or pieces of information about the situation and participants.Decisions select from alternatives, typically to find the one most profitable or appropriate for an organization.Decisions result in an action being taken, not just knowledge being added to what’s knownThe basic decision making process is simple. Data is gathered on which to base the decision. Some analysis of this data is performed and rules derived from company policy, regulations, best practices and experience is applied. A course of action, a selection from the possible options, is then made so that it can be acted on. When considering decisions in operational business processes, the way the decision is made is often constrained such that it can be described and automated effectively in many, even most, cases.
  • As we are talking about decisions it is worth remembering that all decisions matter, as Peter Drucker noted. Not just the big, strategic decisions of your executives but the day to day decisions that drive your business.
  • Volume—Perhaps the most common characteristic of operational decision problems is that the number of decisions of a particular type you must make is high—so high you must automate it or high enough that many front-line workers must make it on your behalf. Volume alone can cause problems or exacerbate another decision problem, such as compliance or risk assessment. Latency—Many managers now have more timely information about their business. If you can use this information to see trouble coming but can’t change how you make decisions in time, you might have an operational decision problem. The latency between knowing something must change and being able to change it probably comes from having systems or people processes that are hard to change quickly. This is often caused by the way operational decisions are handled.Variability—Try imagining nightmare scenarios and thinking about what approach you might take. Think about the systems and people interacting with associates. Decisions those systems and people affect that must change to reflect your new approach could well be operational decisions that, although not a problem now, would cause problems if the business climate changed suddenly.Compliance—Ensuring that decisions are made consistently by using the same set of guidelines and policies and being able to prove to regulators that the correct rules are in place and used for a given decision can be difficult, especially if the decision must be made in any sort of volume. Demonstrating compliance in every operational decision can be particularly time-consuming if the decision isn’t automated correctly.Straight-through processing—“Straight-through processing” or “once and done” processing involves performing every step in a transaction or process without human intervention. A manual review that drags down response time in a process might be hiding a problem-prone operational decision. If you have a mostly automated process that hangs up on manual reviews, you might have a good candidate for an operational decision.Managing risk—A prime reason for having a person involved in a process is to manage risk, which is often all about making decisions that manage trade-offs or risks and rewards. A risk-centered decision that must be made quickly or in volume might be a good candidate for an operational decision.Unattended—With some transactions, there’s no choice but to automate a decision. Without automation, there’s no way to inject expertise or learn what works better and improve the decision; for example, there’s no person who can make a decision in transactions on your Web site or at your ATM. These kinds of decisions are often good candidates for operational decisions.Self-service—Complex decisions are more common in self-service. No longer is it enough for a self-service portal to deliver a document or ask someone to call an 800 number when things get complex. Now you need to automate this decision so that customers can self-serve, even when the decisions involved are complex.Personalized—Any time you want to personalize interactions with associates, you’re making a decision. For most organizations, these operational decisions can create problems because of the need to balance timeliness with personalization. (Taylor and Raden 2007)
  • much of a typical mainframe system is static, works fine and needs no maintenance. Often only a small portion of the system is responsible for much of the maintenance work. My suggestion would be to find the COBOL that represents business decisions such as a pricing engine (what price is this product for this customer), eligibility logic (is this customer eligible for this offer or service), approval rules (can this claim be auto-approved) and replace those parts of the application with Decision Services.
  • Remember – decisions are where the business, analytics and IT all come together
  • The consequences of this are 5 foldFirst we isolate decisions so that they can be managed and controlledThis allows the high-change, complex logic elements of legacy applications to be externalizedIt gives us points of control and agility in processesIt allows for the easy integration of analyticsMost of all, it puts the business in control of decisions even when those decisions are being automated and delivered into our applications.One of the interesting facts about Decision Management is that it was created by studying history and observing what worked – I know as I was there. This was not an attempt to describe a new thing but to give a label to an old thing – something that worked and worked well in a particular environment because it seemed that the things that had limited it to this niche – hardware cost, performance, software techniques – were a thing of the past.
  • People make decisions based on prior experience and expertise.People make decisions based on pre-conceptions and biases.People make decisions based on policies and regulations and their understanding of them.People make decisions based on historical information and their analysis of itPeople make decisions based on context
  • Here’s the stack again just to be clear.But #39 is important here too – managing readiness and organizational change.
  • So making decisions correctly will be hard unless we can pull all these rules together.Given this is how rules often look to start with, this is clearly going to be hard.But rules also change…Because your business policies doBecause your competitors doBecause the law doesBecause stock levels doBecause your services and products doBecause your customers doBecause your customers’ needs doSo we need something that will let us collect, manage and update the business rules that drive our decisions
  • Customer ChurnCustomer Service CallsLoss to CompetitorsRetention Budget
  • Let’s take a process like completing the sale of a subscription service, a location-dependent one like a cell phone, and see what decisions are part of that process. The process involves a customer specifying the service they want, answer questions about themselves and then either getting accepted or rejected.In this process there is clearly a decision – can this customer buy this service. We can drill into this a little. To determine if a customer is eligible for a service we might do several things. First we might check to see if the service they want is available in their area, we might check to see if we still have capacity on the service and then we will see if the information provided by the customer makes them eligible for the service. So now we have a decision with three rulesets or sub-decisions:Can this customer buy this service?Is the service available where the customer livesIs there capacity on this service?Is the customer eligible for the service?Interestingly we can immediately see that the first of these might be one we want to expose as an independent decision so that a customer can check to see if a service in which they are interested is available in their area. Similarly we might combine the first two for a customer service representative to answer a customer question. The difference here is that we might not want to expose problems with capacity too casually.Returning to our process we might decide that we don’t just want a yes/no we want what I call a “yes and/no but” decision. In other words we want to say yes when we can but also see if there is a cross-sell/up-sell that makes more sense. Similarly if we would have to say no we want to be able to say no but you can get this product (presumably something similar).Now we have a second decision – what is the best upsell/cross-sell for this service for this customer. This would take customer information and a service (one already approved for them) and return either a replacement service (an upsell) or an additional service (a cross sell). This decision probably has two sub-decisions:What is the best upsell/cross-sell for this customer when buying this service?Is there a replacement service that is a compelling upsell for this customer for this service?Is there a cross-sell/additional service for this customer when buying this service?And if the first one returns a new, upsell service then the cross-sell would need to be executed against the upsell service.And we have a third decision – what is a similar decision for this customer when rejected for this service. This too has two sub-decisions:what is a similar decision for this customer when rejected for this servicewhat services are similar to this service?which services (from a list) is this customer eligible for?Interesting the second sub-decision uses the same rules as the eligibility check mentioned earlier but takes a set of services to check not a single one. Also we might choose to expose the what services are similar decision as a decision so that a customer looking at a particular service would see a list of “other services you might want to consider).Finally we might decide that pricing is not static for these services and so add a decision what is the price for this service for this customer at this time? This could use things like promotions, customer profile and existing products/services owned to calculate a discount etc.

Importance of decisions OMG Importance of decisions OMG Presentation Transcript

  • On the importance of decisions
    James Taylor,
    CEO
  • Your presenter – James Taylor
    CEO of Decision Management Solutions
    Works with clients to improve their business by applying analytics, business rulesand decisioning technology to automate and improve decisions
    Spent the last 8 years developing the concept of Decision Management
    20 years experience in all aspects of software including time in FICO, PeopleSoft R&D, Ernst & Young
    2
    ©2011 Decision Management Solutions
  • Decisions and smarter systems
    Different kinds of decisions
    Introducing Decision Management
    Business Rules and Decision Management
    Analytics and Decision Management
    Wrap and next steps
  • The one slide you need
    Smarter systems must make more decisions
    Decisions can be strategic, tactical or operational
    Operational decisions are critical
    Operational decision services use
    business rules
    data mining and predictive analytics
    optimization
    The technology works but the design tools and methodology are lacking
    4
    ©2011 Decision Management Solutions
  • Decisions and smarter systems
  • Mainstream applications
    Built to last, not to change
    Report but don’t learn
    Wait rather than act
    6
    ©2011 Decision Management Solutions
    BOSS
    Local exceptions Global standards
    Escalate rather than empower
  • Manual
    Not Made
    Managed
    Before
    After
    Managed
    Manual
    Not Made
    New
    Larger boxes represent more decisions, by volume
    They must make more decisions
    7
    ©2011 Decision Management Solutions
  • Different kinds of Decisions
  • ©2011 Decision Management Solutions
    9
    What is a decision?
    Data is gathered, considered
    A choice or selection is made
    That results in a commitment to action
  • ©2010 Decision Management Solutions
    10
    Different kinds of decisions
    Type
    Strategy
    Tactics
    Operations
    Economic impact
    Low
    High
  • ©2010 Decision Management Solutions
    11
    Operational decisions matter
    “Most discussions of decision making assume that only senior executives make decisions or that only senior executives’ decisions matter. This is a dangerous mistake.”
    Peter Drucker
  • There are many dimensions of decisions
  • ©2011 Decision Management Solutions
    13
    Operational decisions are different
    After Smart (Enough) Systems, Prentice Hall 2007
  • ©2011 Decision Management Solutions
    14
    Operational decisions in your systems
    Examples:
    Determine if a customer is eligible for a benefit
    Validate the completeness of an invoice
    Calculate the discount for an order
    Assess the risk of a transaction
    Select the terms for a loan
    Choose which claims to Fast Track
    These are decision words
    The system must answer a question each time
  • Regulations change
    Policies change
    Competitors change
    Markets change
    Consumer behavior changes
    Fraudsters adapt
    Change to keep eligibility decisions compliant
    Change validation to track new data requirements
    Change the discount to remain competitive
    Change the assessment to manage risk
    Change to keep selecting the right deal terms
    Change the routing to focus on new fraud
    Decisions are high change components
    15
    ©2011 Decision Management Solutions
  • Operational decisions are at the center
  • Introducing Decision Management
  • ©2011 Decision Management Solutions
    18
    Decision Management
    An approach or business discipline for automating and improving decision-making
    It improves day to day business results by
    Supporting
    Automating and
    Improving operational decisions
  • ©2011 Decision Management Solutions
    19
    Delivering Decision Management
    3 stages to better operational decisions
    Create a “closed loop” between operations and analytics to measure results and drive improvement
    Design and build independent decision processes to replace decision points embedded in operational systems
    Identify the decisions (usually about customers) that are most important to your operational success
  • Consequences of Decision Management
    Business Control of Decisions
    Simpler, more agileBusiness Processes
    Integration of Business Analytics
    Externalization from Legacy Applications
    Separation of Decisions
  • Decision Management, Decision Support
    100%
    Decision Management
    OperationalDecisions
    TacticalDecisions
    StrategicDecisions
    Decision Support
    0%
    Decision Volume Increases
    Smart (Enough) Systems, Prentice Hall June 2007. Fig 2.3
  • ©2010 Decision Management Solutions
    22
    How people make decisions
    Analysis of Information
    Expertise
    and
    experience
    Pre
    -
    conceptions
    & biases
    Context
    Policies and
    regulations
  • ©2010 Decision Management Solutions
    23
    The Decision Management stack
    Business Process Management, Business Event Management
    Web Services
    PerformanceManagementKPIs
    DatabaseData WarehouseVisualizationBI
    Decision
    Analysis
    Decision Service
    PredictiveAnalytics
    DescriptiveAnalytics
    Optimization
    Business Rules
    In-Database
    Analytics
    Enterprise Platform
  • Business Rules and Decision Management
    ©2011 Decision Management Solutions
    24
  • What are business rules?
    “… statements of the actions you should take when certain business conditions are true.”
    25
    ©2011 Decision Management Solutions
  • Business rules drive decisions
    ©2011 Decision Management Solutions
    26
    Decision
    Policy
    Regulations
    History
    Experience
    Legacy Applications
  • public class Application {private Customer customers[];private Customer goldCustomers[];...public void checkOrder() { for (inti = 0; i < numCustomers; i++) { Customer aCustomer = customers[i]; if (aCustomer.checkIfGold()) {numGoldCustomers++;goldCustomers[numGoldCustomers] = aCustomer; if (aCustomer.getCurrentOrder().getAmount() > 100000)aCustomer.setSpecialDiscount (0.05); } }}
    Unmanageable business rules
    27
    ©2011 Decision Management Solutions
  • Manageable business rules
    Smart (Enough) Systems, Prentice Hall June 2007. Fig 4.3
    28
    ©2011 Decision Management Solutions
  • A Business Rules Management System
    RuleRepository
    Operational
    Database
    Testing
    Validation and Verification
    DecisionService
    Deployment
    ProductionApplication
    Rule Engine
    DesignTools
    RuleManagementApplications
    After Smart (Enough) Systems, Prentice Hall June 2007. Fig 6.6
    29
    ©2011 Decision Management Solutions
  • Analytics and Decision Management
  • Analytics simplify data to amplify its meaning.


    31
    ©2010 Decision Management Solutions
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    DataMining
    PredictiveAnalytics
    BusinessIntelligence
    Knowledge - Description
    Action - Prescription
    32
    ©2010 Decision Management Solutions
  • Predictive analytics turn uncertainty into usable probability.


    33
    ©2010 Decision Management Solutions
  • ©2011 Decision Management Solutions
    34
    Analytics power operational decisions
    How do I…
    prevent this customer from churning?
    convert this visitor?
    acquire this prospect?
    make this offer compelling to this person?
    identify this claim as fraudulent?
    correctly estimate the risk of this loan?
    They help make better operational decisions
  • HighIncome
    High income,low-moderate education
    *
    Moderate-high educationlow-moderate income
    *
    Low-moderateincome, young
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    Moderate education,low income, middle-aged
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    High
    Low education,low income
    ©2010-2011 Decision Management Solutions
    35
    Insights must drive action
    Business Rules make analytics actionable
    Analytic insights are deployed via a BRMS built in a Decision Service, making them actionable.
  • Wrap up and next steps
  • ©2011 Decision Management Solutions
    37
    Integrate operational and analytic
    Operational Systems
    Business Rules
    Analytics
    AnalyticSystems
  • ©2011 Decision Management Solutions
    38
    Standards
    BPMN
    BMM
    SBVR
    PRR
    PMML
  • ©2010 Decision Management Solutions
    39
    Information about a decision
    Basic decision details
    Name
    A question for the decision and a defined set of answers in natural language
    Decision type
    Any other results to be returned with the answer
    Relevant decision points and any variation across these
    Description
    Key facts like volume, complexity, latency
  • ©2010 Decision Management Solutions
    40
    Decision to KPI mapping
  • ©2010 Decision Management Solutions
    41
    Decision decomposition example
    What is the price of this service?
    Can this customer buy this service?
    Customer Profile
    Is the service available where this customer lives?
    Promotions
    Is there capacity on this service?
    Pricing rules
    Is the customer eligible for this service?
    Geographical Availability
    Eligibility rules
    Capacity and Usage
    Purchase propensity
    What is the best up sell/cross-sell for this customer?
    Is there an additional service?
    What similar service is this customer eligible for?
    Is there a compelling replacement service?
    Which services is the customer eligible for?
    What services are similar to requested service?
    Churn risk
    Product hierarchy
  • ©2011 Decision Management Solutions
    42
    The one slide you need
    Smarter systems must make more decisions
    Decisions can be strategic, tactical or operational
    Operational decisions are critical
    Operational decision services use
    business rules
    data mining and predictive analytics
    optimization
    The technology works but the design tools and methodology are lacking