Smart decisions and processes - GSE Young Professionalsgsebelux.com/system/files/GSE-2016-JV.pdf ·...
Transcript of Smart decisions and processes - GSE Young Professionalsgsebelux.com/system/files/GSE-2016-JV.pdf ·...
Smart decisions and processes
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Jan Vanthienen KU Leuven, Leuven Institute for Research in Information Systems [email protected]
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*Jan Vanthienen
KU Leuven Faculty of Economics and Business Business Information Systems Group
Research and teaching: • Business rules, processes and information systems • Information & Knowledge Management
• Decision models & tables
• Business intelligence & Analytics
IBM Faculty Award
Belgian Francqui Chair 2009 at FUNDP
- Bpost bank Research Chair Actionable Analytics
- Colruyt-Symeta Research Chair Smart Data and Decisions in Marketing
- IBM Fund Intelligent Business Decision Making
- Microsoft Research Chair on Intelligent Environments
- PricewaterhouseCoopers Chair on E-Business
Email: [email protected]
LIRIS (Leuven
Institute for
Research in
Information
Systems)
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Smart decisions and processes
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■ For internal use?
■ Producing external data?
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Main Entry: in·tel·li·gence
Pronunciation: in-'te-l&-j&n(t)s
Etymology: Middle English, from Middle French, from Latin intelligentia,
from intelligent-, intelligens intelligent
1 a : INFORMATION : the ability or agency to obtain the necessary information;
1 b : COMPREHENSION : the act of understanding and abstraction;
1 c : COMMUNICATION : the capacity to communicate accurately,
2 : ADAPTABILITY : the power to adapt to the environment, also : CHANGE, INNOVATION;
3 a : LEARNING : the capability to learn;
3 b : REASONING : the ability to reason;;
4 : EFFECTIVENESS the aptitude to perform functions;
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Summarize what happened, see patterns, reduce
data, derive information from data, understand.
Insight into the past (“What has happened?”)
Associations, Sequences and Clustering
Cross-selling
Segmentation
Text clustering
Risk profiles
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Forecast what will might happen in the future:
predict data you don’t have, based on data you have.
Understanding the future. (“What could happen?”)
Classification and Regression
Customer churn & retention
Sentiment analysis
HR Analytics
Response Modeling
Bankruptcy
Credit scoring
+ -
y > 7?
No Yes
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x < 3?
No Yes
y < 5?
No Yes
x < 1?
No Yes
+ -
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KNOWLEDGE
INFORMATION
ORGANIZE
ANALYZE
DATA
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Data mining
Process mining (including event times)
Age Car Type Risk
27 Sports
34 Minivan
55 Family
34 Sports
Age Car Type Risk
20 Combi High
18 Sports High
40 Sports High
50 Family Low
35 Minivan Low
30 Combi High
32 Family Low
40 Combi Low
Risk
High
Low
Low
High
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Recommending one or more courses of action -- and
showing the likely outcome of each decision.
Able to predict the possible consequences and
recommend the best course of action for any pre-
specified outcome. (“What should we do?”)
Optimization and simulation
Business rules
Advice on what action to take
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Data
Information
Knowledge
Action
Collection
Decisions
Integration
Analysis
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Strategic decisions
• Do we enter the insurance market?
• Should we sell travel insurance?
Tactical decisions
• Which products will we promote?
• How to measure and manage performance?
Operational decisions
• How to handle routine cases?
• Follow known rules
Decision execution
• Handle the cases
• Execute the model
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Business event
Action Time
Cap
turing
Rep
orting
Decision
latency
Busin
ess V
alu
e
Analysis completed
Action taken
(based on: Richard Hackathorn, Bolder Technology, Inc)
Information delivered
Data captured
Analysis
latency
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Data
Process
Rule
Football
Decisions
Access
Banking
Insurance
Travel
Taxes
Advertising
Premiums
Legal
Sales
Production
Health
Allowances
Where are the
rules of the
business …
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Vocabulary
Processes
Rules
Any business …
Concepts Ludo (from Latin ludo, "I play") is a board game for two to four players, in
which the players race their four tokens from start to finish according to die
rolls.
Each player is assigned a colour and has four tokens of matching colour
The board is normally square with a cross-shaped game track, with each arm
of the cross consisting of three columns of squares.
Rules
Two, three, or four may play. The first to bring all their tokens to the finish
wins the game. A player may not end his move on a square he already
occupies. If the advance of a token ends on a square occupied by an
opponent's token, the opponent token is returned to its owner's yard. The
returned token may only be reentered into play when the owner again rolls a
6.
How to play?
Each player rolls the die, the highest roller begins the game. The players
alternate turns in a clockwise direction.
To enter a token into play from its staging area to its starting square, a
player must roll a 6. Once a player has one or more tokens in play, he selects
a token and moves it forward along the track the number of squares
indicated by the die roll.
Strategy and tactics
Although Ludo is mainly determined by chance, some strategic elements are
present. When a player has two or more tokens in the game, he or she can
choose the one to play with.
Strategy
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Decisions are important for business, not only processes.
Why would we only model the processes or the data?
* Where is the decision?
How is the decision logic modeled?
* Model the Decision activity: Decide acceptance
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?
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Decision trees should not be process paths
* Do not hardcode decision rules
into the process model
* Separating (decision) rules
from the process
simplifies the process
* Simplify nested decision paths:
Decide applicant type
Applicant type depends on:
o Age
o (and in some cases also Medical Record)
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refuse highrisk applicant
accept low riskapplicant
Good Medical Record
Age<20
21<=Age<50
Age>=50
Bad Medical Record
acceptmedium risk
applicant
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(Source: Decision Management Solutions)
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Decision(s) (rules) need to be modeled
* A standard for processes (BPMN)
is not enough
* Decision Modeling & Notation standard
(DMN)
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*Simpler processes
*Different timing of changes
*Improved agility (change decision and keep process)
*Improved visibility and focus
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*Simpler decision modeling and discovery
*Different responsibilities, different
stakeholders
*Reuse decisions across processes
*Automate manual decisions
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Informaton requirement
Knowledge requirement
Authority requirement
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*What is to be decided? Possible outcomes?
*Decisions require: * Input data * Transactions
* Master data
* External data
*Decision logic * Rules, knowledge
* Policies
* Analytics
*Outcome of other decisions * Reusability
*The process of decision making?
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2011: Gwen (from insurance):
“Jan, I attended your presentation last year, and we applied the
ideas you told us. I must thank you. What used to take 5 people
for 5 months is now done by 1 person in 2 weeks or less. And …”
2012: Gwen & Kate :
Actually, it saves the company
2.9 million $
… a year
2013: Hey Jan, good news,
we got promoted this year.
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Sometimes the entire process is about a decision
* Model the decision first, and then think about how to execute it
* The same decision can be processed in many ways
* The process of making a decision depends on the desired criteria (throughput, efficiency, customer comfort, …)
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Start each individual decision activity as
soon as all its preconditions are fulfilled
Avoid superfluous decision activities
(unnecessary work)
Group customer contacts
naturalization
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Business rules constrain and guide the process(es)
* The Process – Rule continuum
* Declarative process modeling, smart BPM, smart decisions, smart business
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Consistent Integration of Decision (DMN) and Process (BPMN) Models, Laurent Janssens, Ekaterina Bazhenova, Johannes De Smedt, Jan Vanthienen, and Marc
Denecker, accepted for CaiSE forum, 2016
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Business decision management
* Modelling, managing and executing the business decisions
* Including Descriptive, Predictive Analytics, CEP (Complex Event
Processing)
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Information
Decision
Action
Business result
Evaluate in model
Update model
Refine Improve
predictors
Update decision
rules
Decision
Management
Analytics
Source: James Taylor
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Data mining
Process mining (including event times)
Integrated mining (including decisions)
Age Car Type Risk
27 Sports
34 Minivan
55 Family
34 Sports
Age Car Type Risk
20 Combi High
18 Sports High
40 Sports High
50 Family Low
35 Minivan Low
30 Combi High
32 Family Low
40 Combi Low
Risk
High
Low
Low
High
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* Transformational issues of big data and analytics in networked business
Baesens B, Bapna R, Marsden J, Vanthienen J, Zhao J, 2016, MIS Quarterly, vol. accepted.
* Mixed-paradigm process modeling with intertwined state spaces
De Smedt J, De Weerdt J, Vanthienen J, Poels G, 2016, Business & Information Systems Engineering, vol. 58, no. 1, pp. 19 - 29.
* Fusion miner: process discovery for mixed-paradigm models,
De Smedt J, De Weerdt J, Vanthienen J, 2015-09, Decision Support Systems, vol. 77, pp. 123 - 136.
* Advanced rule-based process analytics: applications for risk response decisions and management control activities
Caron F, vanden Broucke S, Vanthienen J, Baesens B, 2014, Expert Systems with Applications, vol. accepted.
* Making business environments smarter: a context-adaptive petri net approach
Serral Asensio E, De Smedt J, Vanthienen J, 2014, 2014 IEEE International Conference on Ubiquitous Intelligence and Computing,
pp. 343 - 348.
* Modeling business decisions and processes – which comes first?
Vanthienen J, Caron F, 2014, Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the
International Conference on Knowledge Management and Information Sharing, pp. 451 - 456.
* Multi-paradigm process mining: retrieving better models by combining rules and sequences
De Smedt J, De Weerdt J, Vanthienen J, 2014, On the Move to Meaningful Internet Systems: OTM 2014 Conference, vol. 8841, pp.
446 - 453, Conference on Cooperative Information Systems (CoopIS 2014).
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