OBI Analytics in IBM

IBM Sales & Distribution – Client Process Transformation

© Copyright IBM Corporation 2008

OBI Analytics in IBM:

Building a Global Sense &

Respond Solution Best Practices & Lessons Learned

Paige Poore

Program Executive, IBM

IBM Sales & Distribution Client Process Transformation

© Copyright IBM Corporation 2008Oracle Open World 2008: OBI Analytics in IBM, Building a Sense and Respond Solution | Paige Poore, IBM2

Agenda

CRM in IBM

How OBI EE fits

Our Evaluation & Piloting process

Our Global Implementation

Lessons Learned - or I wish we’d known then, what we know now

Closing remarks



CRM in IBM today

Nearly 60,000 IBMersSeveral thousand Business Partner firms

ibm.com Contact Centers

Service and Support

Business Partners

Field Sales

Marketing

2000 2002 2004 2006 2008

Common global application, using Analytics, is

now enabled in IBM for most customer touch

points

4 CRM instances worldwide

Globally consistent customer focus

Integrating and enabling core business processes

Sales execution metrics drive improvement



Much more than just reporting

a sense and respond approach drives actions to individuals and

delivers daily value to sales reps, providing insight linked to needed

actions

ABC Client team

Dashboard

& Alerts

XYZ Client team

Process Execution Indicators

• # of account plans

• Leads generated from

account plans

• Commitment

management

Solution

Proposal

and

Contract

Creation

• # of leads—metrics

tied to leads rejected,

accepted, turned into

opportunities

• Pipeline quality

Win/loss ratio

Opportunity

Manageme

nt

Lead

Manageme

nt

Relationshi

p

Manageme

nt

Dashboard

& Alerts



Agenda

CRM in IBM, today

How OBIEE Analytics fits

Our evaluation & piloting process

Our Global implementation

Lessons Learned – or I wish we’d known then what we know now

Closing remarks



The CRM Vision – It’s a JourneyIn the beginning, there was chaos

CHAOS

800 CRM applications

40+ CMRs

No common data definitions

No common processes



STANDARDS

Common Process,

Common Data & Data Model,

Common Tool,

Common Management System

Chaos was transformed to order by defining standards

CHAOS



ANALYTICS Proactive alerts and analysis

Integrated into common tool

Auto-generating sensors and alerts

Early market insight

Defined by role

IBM needs actionable information

delivered as close to the client as possible

CHAOS

STANDARDS



The CRM Vision – It’s a JourneyIBM is a living system with tremendous market insight.

Linking business sensors and alerts for action optimizes the business

CHAOS STANDARDS

AUTONOMIC SALES

MANAGEMENT



Agenda

CRM in IBM today

How Oracle BI fits in IBM

Our evaluation & piloting process

Our Global implementation

Lessons Learned – or, I wish we knew then what we know now

Closing remarks



Best Practices –

Our initial investigation occurred in three phases

Prototype

Challenge

Develop analytics

prototype based on

real-life problems

Technical

Assessment

In-depth

architecture

inspection

Scalability

Assessment

High-level systems

and expertise sizing

Interview other OBI

customers

The next step:

Move forward with production Pilot



Best Practices - The production pilot was a practical

application of the program with end users on a production

system over an evaluation period of several weeks

The pilot had to demonstrate

the following functional capability:

Enhanced user productivity

Allowed flexible end-user control

Could offload current reporting and query

workloads that tax the production system

Could easily adopt IBM's security

implementation

Scaled to the same degree as the CRM

implementation in IBM

and…

the following "to-be process" aspects:

Use a sense and respond approach to

inspect data that had been input into the

CRM system in IBM

Deliver a base set of business metrics

that are useful to sales reps and managers,

and that provide insight into their business

Notify the user and/or manager

of data quality exceptions

and out-of-bounds conditions,

prompting their action

The next step:

Expand to a phased internal implementation



Best Practices – Expansion to a Global, World-wide Model

Worldwide model – phased approach

– A single worldwide infrastructure

– Initially deployed in Europe, other 3 followed

– Initial highly motivated business units

– Action-oriented governance model to allow

for rapid decision-making, implementation

Target audience

– Sellers and immediate managers

– Nearly 60,000 IBMers

– Managing customers and several thousand Business Partner firms

– 4 Geographies, WW integration of data

Some Specific Examples















Agenda

CRM in IBM, today

How Analytics fits in IBM

Our evaluation & Piloting process

Our implementation

Lessons Learned (or, I wish we’d known then what we know now)

Closing remarks



Upfront considerations

– Real time capability. Everyone asks for it,

but do they really need it (is there a cost factor)?

In fact, do they really even want it?

Lesson learned: Some BI is more valuable

if it's near real time

– Do you have to start with the latest level of

CRM?

IBM integrated BI with a lower-level

CRM system.

(IBM is upgrading from CRM v7.5 to CRM 8.0)

– Big Bang vs. Just get it out

Caution: avoid analysis paralysis and over design

Oracle Open World 2008: OBI Analytics in IBM, Building a Sense and Respond Solution | Paige Poore, IBM21

Food for thought



Best practices for design / development / deployment

– Best design practices. Do not start with a blank piece of paper!

(Or, How can you help the business figure out what they really want and set them up

for success?A: Use templates; provide limited choices; work in small teams; appoint designated decision

makers. Keep it simple and stick to the plan. Don’t try to build the Taj Mahal

– Best development practices - What is the best way to get it out there and

generate value quickly?A: Prototype approaches; team on business

and development; get iterative feedback (Agile)

– How do you accelerate adoption? If you try to

please everyone, no one will be happy A: Pick your niche for each

rollout. There will be surprising lessons on

sources of your best input; it's not always who

you think...


Potholes to avoid

Or "I wish we knew then what we know now!"



Best practices for design / development / deployment

– How much education/training do you need to provide?

A: Education, training, and increasing usage - tips and techniques, a tough lesson for

us to learn. Don't make the same mistakes we did! It doesn't matter if you're giving

them the best thing in the world on a silver platter - if you need education and training

for your users, you didn't do it right!

– What is your secret weapon for moving quickly and to be successful?

A: High Performing resources – experienced –

expertise... Makes all the difference in how

successful you will be. Do not start with

‘we’ll train as we go resources’. You need

the expertise of a small team that has strong

skills in database management, BI, and GUI

interface design (UCD). And don’t release

them after the first triumph – this is very hard

to recapture, and hard to fix if you let it go.

The right expertise & skills retention


Potholes to avoid

Or "I wish we'd known then what we know now"



BACKUP



The journey toward Analytics started with the move to CRM and

several early challenges in IBM around consolidated reporting

Multiple Approaches

– Multiple, independent shadow reporting approaches

– No integrated reporting solution within our CRM

environment

Limits to Enterprise Information Warehouse (EIW)

– Contains subset of CRM data; Not an operational

management data source

– Ongoing operational challenges with CRM data

extracts, EIW conversions and feeds

Ad hoc reporting is difficult and requires DBA-

type skills to use multiple tools

– Actuate, Brio

– Shadow Database



The discovery period lasted three weeks and focused on defining the

business needs, value, and scope

Targeted greatest value-add to 4 job roles:

– Salesperson, Sales manager, Geography data custodian, Sales operations leader

Capabilities of most interest included:

– Sense and respond alerting

– Marketplace indicators

– Progress monitoring: what’s working, what isn’t

Approval Rating Q: "Is this report of

use/interest for your business unit?"

70%

21%

9%

7.5%-1.00%

>50%

< or = 50%

Focus areas with biggest value items included:

– Face time improvements

– Data quality and reporting problems very high

interest in all Out of the box reports



Our approach to the production pilot used a rapid implementation

method, including iterative development, over a six week period

Sales Analytics out of the box capability and ease-of-use allowed

implementation of more function than originally scoped

plus rapid turnaround by small development team

Original scope Final scope

Sales Analytics

Out of the Box

24 reports: up to 4 dashboards

with up to 6 reports each

60 reports: 15 dashboards with up to 4 reports

each

Customization Out-of-the-box dashboards pre-

configured by Oracle

Minimal customization

14 reports via Answers to address custom requests

1 new data star

10 data exception rules

36 CRM custom extension columns

100+ change requests

Summary 24 reports 60 reports plus 100+ change requests



Feedback from the pilot was positive!

Feedback – Dashboard users

Ease of use, navigation and graphical

display; links on charts was positive.

Ability to summarize data and quickly drill-

down to understand what was driving the

pipeline.

Data quality reports with alerts. Overcomes

key problems on data privacy … reporting

consistency.

Different overviews and direct connections

to opportunity for change.

Significant to user productivity

Feedback - Answers users

Easy to build reports.

Users don't need extensive knowledge of

the data model to design reports.

Data quality checking good.

Strong in-person filtering dimension.

Easier reporting in terms of table structure

and speed of creation.

Filtering to help identify the key actions.

Answers requires more training than

dashboard use.



Pilot Results – Lessons Learned

Key lessons:

– Use best practice, pre-configured

dashboards with limited customization

– Use discovery phase to validate specific

users for deployment and best dashboards

for them

– Iterative development is critical

– Take small steps in the deploy; a few seats

at a time, validate, repeat

– Close teaming

helps ensure success

Key challenges overcome:

– Remote locations of development and user

teams (Atlanta and EMEA, respectively)

– Pilot audience and scope significantly

expanded

– Compliance with European data privacy

requirements

– Performance tuning



The CRM Vision – It’s a Journey

Sense & Respond is a turning point

CHAOS STANDARDS

AUTONOMIC SALES

MANAGEMENT



OPTIMIZATIONDissect key processes

Measure time and effectiveness

Embed KPIs into management system

Track KPIs, Learn, Improve

The CRM Vision – It’s a JourneyQueries, regression analysis, control limits optimize speed and effectiveness,

delivering early insight to market dynamics, process breakdowns

CHAOS STANDARDS



AUTONOMIC SALES MGMT

KPIs kick off actions

Self-correcting system

Optimal resourcing

Fact-based confidence levels

Speed bumps eliminated

The CRM Vision – It’s a JourneyAutomate actionsreduce parts orders to manage backloghire more

Business Partners to shift channel mixlower prices to target competition

CHAOS STANDARDS

Technology

OBI Analytics in IBM