The Evolving Business Process Technology Landscape

transcript

Sandy Kemsley l www.column2.com l @skemsley

The Evolving

Business Process

Technology Landscape

Building Business Capability

Las Vegas 2013

Agenda

l Technology overview and case studies

l Social BPM

l Dynamic/adaptive case management

l Process mining

l Process simulation

l Predictive process analytics

l Preparing for emerging BPM technologies

l New ways of working

l Smarter processes

Copyright Kemsley Design Ltd., 2013 2

How Social Changes

Everything

Technology: Social BPM

Consumer Tools Set Expectations

l Consumption

l Participation

l Creation

l User experience

l Access anywhere

Social BPM Business Benefits

l Weak ties/tacit knowledge exploitation

l Knowledge sharing

l Social feedback

l Transparency

l Participation

l Activity and decision distribution (crowd-

sourcing)

Source: Brambilla et al, “A Notation for Social BPM”

6 Copyright Kemsley Design Ltd., 2013

Collaborative Process Modeling

l Multiple people participate in process discovery, modeling and documentation

l Internal and external participants

l Technical and non-technical participants

l Preserves institutional memory

l Facilitates cross-silo collaboration and innovation

Collaborative Process Modeling

Process Event Streams

l Timeline of activity for social monitoring

l Process models during creation

l Process instances during execution

l Publish/subscribe model to “watch” certain

processes or event types

l Direct link to underlying process model or

instance for unsolicited participation

l Usually mobile-enabled

Process Event Streams

Bank Of Tennessee

Mortgage Processing

Case Study: Social BPM

Case Study: Bank Of Tennessee

l Service-focused regional bank

l Mortgage process before BPM:

l Manual, paper-based

l Long process with bottlenecks and errors

l Many exceptions, constantly changing

l Limited visibility and audit trail

l Search for social collaboration and BPM

platforms merged

Source: Will Barrett, Bank of Tennessee, “Worksocial Pays Dividends”

A Social Mortgage Process

Mobile Mortgages

Bank Of Tennessee: Benefits

l ROI based on social and BPM

l 30% faster to complete process

l Reduced errors

l Process activity stream user interface

l Unified communication channel

l Faster, more efficient actions in place

l Increased adoption/decreased training

l Improved visibility and audit trail

l Critical SLAs visible for action

l Entire process within BPM Copyright Kemsley Design Ltd., 2013 15

The Changing Nature of Work

Technology: Dynamic/Adaptive Case Management

Goals Of Work Types

Routine Work

l Efficiency

l Accuracy

l Process improvement

l Automation

l “Classic” BPM

Knowledge Work

l Flexibility

l Assist human knowledge

l Collect artifacts

l Adaptive/Production/

Dynamic Case

Management (ACM/PCM/

Routine Work

Knowledge Work

Characterizing The Extremes

Routine Work

l A priori process model

l Controlled participation

l Automatable, especially

with service integration,

rules and events

Knowledge Work

l No a priori model

l Collaboration on demand

l Little automation, but

guided by rules and

events

The Structured/Unstructured

Debate

If you can’t model it up front, you just don’t understand

the process

Exceptions are the new normal: every process is different

But It’s Not That Simple

Structured Work

l Some process are that

repeatable, especially

automated processes

l Ad hoc process

exceptions already exist,

they’re just off the grid

Unstructured Work

l Highly variable

processes make

modelling inefficient

l Instrumentation of

unstructured processes

provides value

Dynamic Process Runtime

l User can add participants from own

network or recommended expert

l Non-participant can opt-in to process

l Audit trail captured within BPMS

l Eliminates uncontrolled email

processes

l Captures patterns for

process improvement

Dynamic Process Runtime

Structure Spectrum

Structured

• e.g., automated regulatory process

Structured with ad hoc exceptions

• e.g., financial back-office transactions

Unstructured with pre-defined fragments

• e.g., insurance claims

Unstructured

• e.g., investigations

Norwegian Food Safety Authority

Food Safety Inspections

Case Study: Adaptive Case Management

Case Study: NFSA

l Ensuring food safety, animal/plant welfare:

l Scheduled inspections and events

l Emergency response

l Maintain food safety history

l Apply complex regulations

l Case folder with dynamic worklist

l Case = person/establishment, e.g., farm

l Tasks created dynamically as required,

manually or triggered by events

Source: Computas

NFSA: Dynamic Task Selection

NFSA: Benefits

l Entire food safety history for each

establishment

l Two dynamic case management modes

l Control activity module for regular activities with

full domain data

l Emergency response module with alerts and

follow-up tasks

Discovering Hidden Process

Technology: Process Mining

Process Mining – Sources

BPMS Event Log Format

Copyright Kemsley Design Ltd., 2013

Trans. ID Activity Start Time End Time Resource

8287 Enter customer

08:34:15 08:37:44 User jsmith

8287 Check credit 08:37:52 08:38:05 Equifax service call

1399 Enter customer

08:37:59 08:44:40 User sjones

8287 Enter order 08:38:09 08:38:39 ERP system call

1399 Check credit 08:44:58 08:45:06 Equifax service call

Combining All Event Logs

Trans.

Activity Start

Resource

8287 Enter customer

08:34:15 08:37:44 User jsmith

8287 Create

customer

record

08:34:25 08:35:55 User jsmith

8287 Create address

record

08:36:12 08:37:39 User jsmith

8287 Check credit 08:37:52 08:38:05 Equifax service

8287 Check PO 08:38:10 08:38:15 System

8287 Create order 08:38:18 08:38:31 System

Generating A Process Model

Generated Model Data

Working With Process Mining

Results

l Actual flows, not idealized models

l Frequency and duration of each path

l Optimization:

l Detect main flows and common variations

l Detect loopbacks and other inefficiencies

l Detect wait times

l Analyze variations over time

AkzoNobel Decorative Paints

Procure-To-Pay Process

Case Study: Process Mining

Case Study: AkzoNobel

l Procure-to-pay implemented in SAP

l Process variants based on country-specific

practices

l Need to improve efficiency:

l Remove undesirable variants

l Incorporate local best practices into global

standardized process

Source: Cap Gemini, “Process Mining for Value Extraction”

Extract/Analyze SAP Log Data

AkzoNobel Benefits

l Insight into exception processes

l Comparison between countries and

identification of best practices

l Direct insight for process improvements

l Compliance control compared to corporate

guidelines

Charting A Course In Uncertain

Conditions

Technology: Process Simulation

Model-Simulate-Analyze-Optimize

Simulation Goals

l Test and validate process models

l Establish path patterns

l Estimate end-to-end times

l Optimize resource utilization and SLA

performance across peak/slack periods

l During runtime, predict performance based

on realtime analytics

Simulation in the BPM Lifecycle

William Grant & Sons

Distillery Vat Scheduling

Case Study: Process Simulation

Case Study: William Grant & Sons

l Increased demand and product range

exceeded capacity

l 83 product types

l 22 process paths

l Planned $1.2M investment in additional

distilling vats

Source: SIMUL8

Simulation Scenarios With

Variable Vats, Paths, Rules

William Grant & Sons: Benefits

l Identified low utilization rates for production

l Avoided $1.2 investment through

production rescheduling

l Planning for simulation-driven scheduling

to automate high utilization

Smarter Processes for

Smarter Outcomes

Technology: Predictive Process Analytics

Why Predictive Processes?

“Predictive analytics is not just about

forecasting what’s coming down the pike.

It’s also about keeping the bad alternative

futures from happening.”

James Kobielus, Forrester

Process + Analytics + Decisions =

Intelligent Processes

Business Process

Business Intelligence

Business Rules

Process Analytics in a BPMS

l Executing

process

l Realtime

process

dashboard 52

Critical Path Perspective

Review order

and notify

customer

Select product

Prepare

invoice

Pack product

Ship product

and invoice

ID Task Name Start Finish DurationJun 3 2012

4 5 6 7 8

1 1d04/06/201204/06/2012Review order and notify customer

3 2d06/06/201205/06/2012Select product

4 3h07/06/201207/06/2012Pack product

5 1d 3h06/06/201205/06/2012Prepare invoice

7 4h08/06/201207/06/2012Ship product and invoice

2 0d05/06/201205/06/2012Order confirmed

6 0d07/06/201207/06/2012Ready for shipping

Focus On The Goal, Not The Task

l Compare:

l Current to baseline model

l Current to historical

l Analyze:

l Process dependencies and critical path

l Simulate to identify future problems

l Act:

l Self-adjust through feedback to decisioning

l In-process user guidance

What You Can Do With

Process Analytics

l Information to support manual decisions

l E.g., display queue sizes to help manager to

reallocate work

l Data to trigger automated actions

l E.g., spawn fraud detection process when

series of events occur for same customer

l Predict missed SLAs

l E.g., compare history of activity timeline to

estimate overall time to completion

Preparing For The Big Shift:

New Ways Of Working

The Future Of Business

l Processes need to be:

l More engaging

l More adaptable

l More transparent

l Smarter

Participatory Culture

l Time and resources explicitly allocated

l For collaboration

l For co-creation

l All stakeholders expected to participate

l Appropriate tools provided

l Input considered regardless of level and

technical skills of participant

Transparency And Openness

l Allow internal users to see all information

l Set open as default, override for specific

exceptions

l Allow access to external stakeholders

l Customers, business partners should see their

own information

l Enables easier knowledge dissemination

l Provides context for problem-solving and

collaboration

Management Style Of Trust

l Allow workers to deviate from pre-defined

workflow when appropriate

l Management must allow sufficient autonomy

l Workers must feel comfortable

creating/modifying processes

l Allow workers to collaborate with resources

of their choice

l Assign work or ask assistance

l Internal and external

Rewards And Incentives

l Set expectations for participation

l Reward for collaboration and process

improvement

l Reward for customer service over

efficiency

l Reward teamwork over individual effort

Preparing For The Big Shift:

Smarter Processes

Making Processes Smarter

l Add instrumentation to processes and

harvest big data

l Apply statistical analysis

l Understand cause and effect

Summary

The Future Of Business

l Processes need to be:

l More engaging

l More adaptable

l More transparent

l Smarter

Sandy Kemsley

Kemsley Design Ltd.

email: sandy@kemsleydesign.com

blog: www.column2.com

twitter: @skemsley