© 2009, Hired Brains Inc.

The Agility Imperative

Rethinking BI for Processes

Neil RadenCEO

Hired Brains Inc.

November, 2009

© 2009, Hired Brains Inc. 2

A special thanks to John Patton, CEO, Sight Software,who introduced me to the idea of “Process Intelligence” and with whom I collaborated for this presentation.

jpatton@sightsoftware.com

© 2009, Hired Brains Inc. 3

Business Users Drive AnalyticsPromise of BPM (Business Process Management):

Business users drive the creation, operation and improvement of strategic processes because of enabling technology of (BPM, BPMN, BPEL & SOA)

Also create, use, change and improve process analytics DRM (Domain Reference Model) approach: SAP reference models:

>4000 entity types, 1000 business processes using EPCs; Oracle similar

Only usable by DRM experts. Even configurable reference modeling languages suffer from the same knowledge transfer limitations – stakeholders don’t learn.

© 2009, Hired Brains Inc. 4

DRM of the Sell Process `

© 2009, Hired Brains Inc. 5

Business Users Drive Analytics Today’s BI* for Processes truth: with EPC’s (Event Process Chains)

and DRMs, people can muddle through with pre-defined KPIs and pre-configured BI data models.

Tomorrow’s BI for Processes truth: Today’s BI is ill-suited for a world of agile, interconnected (strategic) processes.

It’s like a square peg in a round hole

* For brevity, we include current data

warehousing methods in the term BI

© 2009, Hired Brains Inc. 6

The State of BI

© 2009, Hired Brains Inc. 7

What Are the Analytical Needs? The Analytic Environment is Different Complex flow data among many agile internal and external

complex processes.

There will be precise, complete end-to-end data on every process instance available in process log files.

Stakeholders require many different views of the processes.

This includes not only flow patterns of process instances, but the resources involved and the process instance data associated with them as well.

© 2009, Hired Brains Inc. 8

What Are the Analytical Needs? If the needs were only tactical, simple dashboard (BAM)

instrumentation would suffice.

But strategic processes require a variety of stakeholders to know with certainty: What happened? What will happen? What could happen?

Processes are complex causal systems with continuously measured flow. (One reason why simplified BI models are poor candidates for root cause analysis and other prescriptive/ predictive analyses)

This implies prediction

© 2009, Hired Brains Inc. 9

What Are the Analytical Needs? The Analytical Methods for Complex Causal Systems

The key strategic questions all involve analyzing process uncertainty.

These methods require that process data: Be presented as distributions Preserve flow (path) information Allow robust time perspectives

Not suited for current BI tools

A simple example

© 2009, Hired Brains Inc. 10

Process Intelligence

IRM

Hotels Convention Venue

How can we get people into the meeting room earlier (so we can start on time)?

© 2009, Hired Brains Inc. 11

LuxorVenetianFlamingoCaesarsBellagio

8:00

7:52

8:04

7:50

8:02

Mean Arrival TimeIRM

© 2009, Hired Brains Inc. 12

LOG FILES LOG FILES

IRMLOG FILESLOG FILES LOG FILES

Process IntelligenceData Persistence Structure:

Process Log Files

© 2009, Hired Brains Inc. 13

CaesarsVenetian

BellagioLuxorFlamingo

FrequencyCount

Arrival Time

Process Intelligence Analytical Primitive:

Distributions

© 2009, Hired Brains Inc. 14

LOG FILES

IRMLOG FILESLOG FILES LOG FILES LOG FILES

Process IntelligenceAnalytical Primitive:

Process Trace

© 2009, Hired Brains Inc. 15

EDM

Convention VenueHotels

Process IntelligenceAnalytical Primitive:

Process Trace

© 2009, Hired Brains Inc. 16

LuxorVenetianFlamingoCaesarsBellagio

8:00

7:52

8:04

7:50

8:02

Mean Arrival TimeEDM

© 2009, Hired Brains Inc. 17

What Approach Will Work? Answer:Process Intelligence

Subtext: Process Intelligence is a distinct product with a distinct market.

Tech Truth: Process event log files are different.

Traffic in distribution not aggregated data

Today’s state-of-the-art solutions for business process intelligence depend on a traditional query-based approach against a relatively static data model and a tough-to-configure data warehouse

© 2009, Hired Brains Inc. 18

Shortcomings of Current Data Warehousing PracticesShortcomings of Current Data Warehousing Practices

Then you have to jackhammer them up

Data warehouse data model designs only fluid when being poured

© 2009, Hired Brains Inc. 19

PDW Pre-processing

PDWSchema

Process Log Files

Process View BPIProcess ViewProcess View

The problems with this tortured OLAP cube-based approach to process analytics are:

Distributions cannot be used as analytical primitives

The process flow model is destroyed in creating the data model

Time is poorly represented

It is not agile

Process flow predictions are crude and inaccurate

Process Log Files Process View

Process Log Files

Process ViewProcess View

Process Log Files Process View

Mapping & correlation of events and data

Process Log Files

© 2009, Hired Brains Inc. 20

Process Intelligence, a distinct technology, provides business and other users the tools necessary to use the proper methods of strategic process analysis:

Automatic instrumentation of BPMN-modeled processes

Analytical primitives that are distributions

Agile process views

Robust time perspectives

Imbedded analytical methods (of complex causal systems)

Accurate flow predictions with full uncertainty

Simplicity

What Approach Will Work?

© 2009, Hired Brains Inc. 21

Process Intelligence Is A Better Solution

Process Intelligence is the right solution for enterprises’ need for agile strategic analysis of process flow through heterogeneous process islands.

Mapping & correlation of events and data

Process Log Files Process Intelligence

What Approach Will Work?

© 2009, Hired Brains Inc. 22

What Are the Analytical Needs? Summary BI was not built for agile, strategic complex causal systems

Strategic processes require analytic agility not available in current BI

Analyzing complex causal systems in an agile environment is beyond the capability of current BI

© 2009, Hired Brains Inc. 23 23

Three Basic Kinds of Analytics

Type Used to: Example1Descriptive

AnalyticsClassify or categorize individuals or other entities

Cluster model

2Predictive Analytics

Predict future behavior of individual

Score

3Decision Analytics

Develop superior ruleset or strategy

Strategy optimization

They can be used together and often are.

© 2009, Hired Brains Inc. 24 24

More Sophisticated Analytics Improve Results

Decision Optimization

XX

XX

XX

X XX

XX

XX

XXX X

XX

XXXXX X

X

X XXX X

XX

X

XX

X

XX

XXXXX X X

X XXX X

XX

XX X X

X X

X

XX X

XX

X

X

XX

Predictive ModelingDescriptive Analytics

How do I use data to learn about my processes ? Where are there areas for improvement?

How are those processes likely to behave in the future? How do they react to the myriad ways instantiated?

How do I leverage that knowledge to extract maximum value from my operations?

Knowledge - Description Action - Prescription

© 2009, Hired Brains Inc. 25 25

Descriptive Models Identify Relations

Use: Find the relationships between events

Example: Sort events into groups with different characteristics and outputs.

Operation: Analysis is generally done offline, but the results can be used in automated decisions – such as switching a supplier in real time

Descriptive models can be used to categorize events into different categories – which can be useful in setting strategies and targeting treatment.

© 2009, Hired Brains Inc. 26 26

Predictive Models Calculate Risk Or Opportunity

Use: Identify the odds that a route will require a specified cycle time

Example: Will the supplier deliver on time? Will the process modification deliver the desired result?

Operation: Models are called by a business rules engine to “score” an individual or transaction, often in real time

Predictive models often rank-order events. For example, cycle time scores rank-order suppliers by their risk – the higher the score, the more “good” supplier for every “bad” one.

© 2009, Hired Brains Inc. 27 27

Decision Models Design Better Strategies

Use: Design a ruleset that will deliver the right decisions to reach goals

Example: Identify how much money to spend on each marketing channel to maximize sales in a given timeframe and budget

Operation: Decision models are used offline to develop rules, which can then be deployed to operate in real time

A decision model maps the relationships between the data available, the decision itself, the outcomes of the decision and the business objective. It is ideal for balancing multiple objectives and constraints.

© 2009, Hired Brains Inc. 28

Data Mining - Improve Rules

**

*

***

* ***

*

* ***

*

*

*

*

* ** *

**

*

* **

**

*

*

*** *

**

* * *

***

*

* *

**

***

**Low-moderateincome, young

HighIncome High income,

low-moderate education

Moderate-high educationlow-moderate income

High

Moderate education,low income, middle-aged

Low education,low income

Education

Age

High

© 2009, Hired Brains Inc. 29

Predictive Analytics – Add Insight

10

20

30

40

Member completes treatment

Member fails to complete treatment

© 2009, Hired Brains Inc. 30

Impact May Take Time to Play Out

© 2009, Hired Brains Inc. 31

Unknown Optimal Approach

Single Approach

Decision SpaceConsidered

Unknown Optimal Approach

Champion

Challenger 1

Challenger 2

Decision SpaceConsidered

Continuous Improvement with Adaptive Control

© 2009, Hired Brains Inc. 32

Contact InformationNeil Raden

Hired Brains, Inc.1415 Kenwood Road

Santa Barbara, CA 93109

www.hiredbrains.com

nraden@hiredbrains.comWhite papers: www.hiredbrains.com/Whitepapers.pdfLinkedIn: http://www.linkedin.com/in/neilradenBlog: http://www.intelligententerprise.com/blog/nraden.html(Office)   +1 805 962 7391  GMT - 08:00 PST(Mobile) +1 805 284 2322