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)

(c) Jan Vanthienen, 2016 2

mailto:[email protected]

http://www.businessrulesforum.com/world-congress-on-decision-tables.php


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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

+

x < 3?

No Yes

y < 5?

No Yes

x < 1?

No Yes

+ -



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KNOWLEDGE

INFORMATION

ORGANIZE

ANALYZE

DATA

9 (c) Jan Vanthienen, 2016 9

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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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?


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)


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

http://www.tomdavenport.com/books.html#coa


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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


* 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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