Executive Institute Directors AGM - Feb 2017

1. Ask the right questions first
Getting strategic about Sales Acceleration
Hugh O’Byrne – VP Global Sales Centre Excellence - IBM
Barry Magee – Client Analytics, Data Strategy and Transformation Leader

2. Marketing
Identified
Lead Dev
Validated
Sales
Qualified
How to respond?
- use data effectively across the funnel to maximum effect and RoI
What’s the problem?
– activities throughout the funnel are often siloed without integration
Why do we care?
– shift in activity towards top of the funnel => marketing and good targeting essential
Let’s start with what we typically do today
Data Not Insight
Lack of Integration
Tactical not Strategic

3. 1. Opportunities not Productivity
It’s the TIME spent on the ‘other’ 98% of calls that is
seen to kill productivity and is wasted effort
2. Pipeline not Client Feedback
We obsess about pipeline we have and not about what
we learned about the clients we failed to convince
3. Wins not Market Trends
We take the wins and miss the fact that the losses may
mean a shift in market direction
1-2% Outbound Lead Conversion
In a typical Campaign environment we focus on the yield only

4. What do we do differently?
identify &
prioritise
We codify expertise into
models that match clients
with needs and prioritizes
engagement driving sellers
to the right clients
B
All things considered, who is
best customer to engage next?
Ren WinBk
Values
Customer Name Sales Rep NetNew Oppty?
IMT
Rank
Vol
Weight
Average
of
%
Direct
Average
of
%
Indirect
Renewals
Power
Storage
Mob
ICS
WinBack
NoCover
psWAXIT
9
to
5
SWMA
Drop-Offs
HWMA
No
SWMA
ETS
HMC
DataPower
XIV
Storwize
Dell
HP
EMC
Cisco
Juniper
Motorola
Linux
Oracle
Sun
SPECIALIST DISTRIBUTIO Shane Ronan-Duggan No 1 9,302 100 0 0 0 0 0 0 0 52 9,250 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
SIG PLC Brian Royle Yes 2 3,960 0 100 0 22 0 0 21 21 1,151 0 0 1,144 1,102 0 42 0 0 439 0 0 0 0 0 0 0 17 0
ARROW ECS UK LTD Shane Ronan-Duggan No 3 3,575 100 0 0 0 0 0 0 0 0 3,575 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
VR012/PGDS LTD Emma Coyle No 5 3,092 0 100 26 0 0 0 0 0 0 0 22 0 0 0 0 0 0 3,044 0 0 0 0 0 0 0 0 0
NORTHAMBER Shane Ronan-Duggan No 6 2,695 100 0 0 0 0 0 0 0 0 2,695 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
PRUDENTIAL Enda Scanlon No 7 2,356 0 100 0 0 0 0 0 0 157 415 0 754 50 0 0 0 0 980 0 0 0 0 0 0 0 0 0
TRAVELERS MANAGMENT LT Enda Scanlon No 8 2,314 100 0 0 0 0 0 0 0 0 0 22 0 0 0 127 75 0 2,089 0 0 0 0 0 0 0 0 0
IMPERIAL COLLEGE Anthony Murphy Yes 9 2,215 0 100 0 0 44 0 0 0 209 104 0 884 200 0 0 0 0 774 0 0 0 0 0 0 0 0 0
VR050/INTELLECTUAL Del Tillyer Yes 10 2,201 0 100 0 0 87 0 0 21 0 0 0 1,040 0 0 0 0 0 1,032 0 21 0 0 0 0 0 0 0
VR695/KINGSTON UNI Anthony Murphy No 11 2,141 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2,141 0 0 0 0 0 0 0 0 0
WILKINSONS Brian Royle No 12 2,117 0 100 0 0 0 0 0 0 209 311 0 806 0 0 42 0 0 748 0 0 0 0 0 0 0 0 0
ADMIRAL Enda Scanlon Yes 13 1,967 0 100 0 22 22 0 0 21 0 52 0 936 0 62 0 0 0 851 0 0 0 0 0 0 0 0 0
LOGICALIS UK Suneel Talikoti No 14 1,850 100 0 0 0 0 0 0 0 0 492 0 572 0 166 0 0 0 619 0 0 0 0 0 0 0 0 0
MCKESSON HBOC Louise Noone No 15 1,780 98 2 0 0 0 0 0 21 235 0 22 208 100 42 403 0 0 748 0 0 0 0 0 0 0 0 0
VR012/ EUI LIMITED Enda Scanlon No 16 1,732 0 100 0 0 0 0 0 0 0 0 22 0 0 0 85 0 0 1,625 0 0 0 0 0 0 0 0 0
VR012/HARGREAVES L Suneel Talikoti No 17 1,677 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1,677 0 0 0 0 0 0 0 0 0
VR695/INTELLECTUAL Del Tillyer No 18 1,647 0 100 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 1,625 0 0 0 0 0 0 0 0 0
VR522/NISA RETAIL Brian Royle No 19 1,627 0 100 0 0 0 0 0 0 0 492 0 0 0 0 0 0 0 1,135 0 0 0 0 0 0 0 0 0
TECH DATA LIMITED Shane Ronan-Duggan No 20 1,555 100 0 0 0 0 0 0 0 0 1,555 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
APACHE NORTH SEA LTD Sarah Knox No 21 1,551 0 100 0 0 0 0 0 0 0 104 0 442 526 416 21 0 0 0 0 42 0 0 0 0 0 0 0
VR522/SAGA SERVICE Louise Noone No 23 1,494 0 100 0 0 0 0 0 0 0 0 22 0 0 0 234 0 0 1,238 0 0 0 0 0 0 0 0 0
VR695/SURREY COUNT Anthony Murphy No 25 1,260 0 100 26 0 0 0 0 0 0 0 22 0 0 0 0 0 0 1,212 0 0 0 0 0 0 0 0 0
RAILWAY PROCUREMENT James Gray Yes 26 1,256 100 0 0 22 22 0 0 21 78 0 0 858 0 0 127 0 0 0 0 63 0 46 0 0 0 17 0
KIER GROUP PLC Marese Clarke No 28 1,236 92 8 0 0 0 0 0 0 131 104 22 442 125 0 0 0 0 413 0 0 0 0 0 0 0 0 0
NHS LANARKSHIRE Sarah Knox No 30 1,206 0 100 0 0 0 0 0 0 0 0 0 520 200 125 0 0 0 361 0 0 0 0 0 0 0 0 0
C & J CLARK Marese Clarke No 31 1,174 0 100 0 0 0 0 0 0 0 0 0 624 50 458 42 0 0 0 0 0 0 0 0 0 0 0 0
VR012/2 SISTERS GR Brian Royle No 32 1,157 0 100 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 1,135 0 0 0 0 0 0 0 0 0
VR012/ECCLESIATICAL IN Louise Noone No 33 1,156 0 100 26 0 0 0 0 0 0 0 0 0 0 0 21 0 0 1,109 0 0 0 0 0 0 0 0 0
HRG C/O ARGOS Brian Royle Yes 34 1,138 0 100 0 0 0 0 0 21 0 52 0 442 125 166 0 0 0 0 0 105 20 0 0 0 0 206 0
VR695/DUMFRIES & G Sarah Knox No 35 1,111 24 76 26 0 0 0 0 0 0 492 0 0 0 0 0 0 0 593 0 0 0 0 0 0 0 0 0
SAGA GROUP LTD Louise Noone No 36 1,104 0 100 0 0 0 0 0 0 0 78 0 494 0 146 0 0 0 387 0 0 0 0 0 0 0 0 0
HMV RETAIL LIMITED Sarah Knox No 37 1,076 9 91 0 0 0 0 0 0 0 0 0 598 0 478 0 0 0 0 0 0 0 0 0 0 0 0 0
VR012/HAIRMYRES HO Sarah Knox No 38 1,058 0 100 26 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1,032 0 0 0 0 0 0 0 0 0
VR012/ATCORE TECHNOLOG Suneel Talikoti No 39 1,056 0 100 0 0 0 0 0 0 0 0 0 806 0 250 0 0 0 0 0 0 0 0 0 0 0 0 0
SCC Suneel Talikoti No 40 1,035 0 100 0 0 0 0 0 0 0 0 0 520 25 0 0 0 0 490 0 0 0 0 0 0 0 0 0
ECCLESIASTICAL Louise Noone Yes 41 1,022 0 100 0 22 65 0 0 21 0 0 0 468 0 62 21 0 0 361 0 0 0 0 0 0 0 0 0
WILKINSON Brian Royle Yes 42 1,005 0 100 0 0 22 0 0 0 26 492 0 0 0 0 0 0 0 464 0 0 0 0 0 0 0 0 0
HALFORDS LTD Brian Royle No 43 1,004 100 0 0 0 0 0 0 0 340 0 0 338 326 0 0 0 0 0 0 0 0 0 0 0 0 0 0
VR012/PLYMOUTH UNI Anthony Murphy No 44 980 0 100 26 0 0 0 0 0 0 0 0 0 0 0 0 0 0 954 0 0 0 0 0 0 0 0 0
VR695/KIER GROUP LTD Marese Clarke No 46 954 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 954 0 0 0 0 0 0 0 0 0
OCADO Marese Clarke Yes 48 934 0 100 0 22 44 0 0 21 0 0 0 416 250 125 21 0 0 0 0 0 0 0 0 0 0 34 0
VR012/ISLE OF WIGH Anthony Murphy No 49 929 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 929 0 0 0 0 0 0 0 0 0
VR012/HAMPSHIRE COUNTY Anthony Murphy No 49 929 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 929 0 0 0 0 0 0 0 0 0
VR012/IMPERIAL COLLEGE Anthony Murphy No 51 925 0 100 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 903 0 0 0 0 0 0 0 0 0
Attach Hardware Software Multi-Vendor
Channel
integrate &
simplify
We translate the data into
simple, understandable
Reason of Call
visualizations and integrate
into Sales Connect
C
What is the data-driven
reason of call?
observe &
adjust
End-to-end management
system on all outcomes
allowing continual course
correction to maximize
performance
D
Where are the clusters of
best opportunity found
A
aggregate &
analyse
We aggregate
thousands of data points
most valuable as lead
indicators of need into a
central repository.
What are the best lead
indicators of client need?
20%
steady state lead conversion rates
compared with 5% average for outbound
100+
disparate lists streamlined into 1 outbound
funnel saves almost 1 hour per rep per day

5. Why? - integrated feedback allows for Marketing and Sales sprints
observe &
adjust
observe &
adjust
observe &
adjust
observe &
adjust
2%
10%
Time
Lead
Conversion
1. create processes to capture the data to answer what you need to know
2. think agile marketing and sales with a data backbone
3. identify > execute > observe > adjust > repeat
4. short sprints of activity allow you course correct more quickly - eliminate waste & maximise conversion

6. Industry Description
Cloud
Count
of
Oracle
HW
Linux
Data
Center
Security
Big
Data
Oracle
Sun
Mainframe
Power
HP
WinTel
Automotive 1 1 4 1
Banking 1
Chemicals & Petroleum 1 1 1
Computer Services 2 2 1 4 4
Consumer Products 2 3 6 10 5
Education 1 1
Electronics 1 1 4 6 7 4 1 6 1 5
Energy & Utilities 1 1 1
Financial Markets 1 2 1 2 2
Government, Central/Federal 1
Healthcare 1 5 1 7 2 4 1 2
Industrial Products 2 4 14 25 2 1 2 31 1 13
Insurance 2 1 2 1
Life Sciences 2 3 1 1
Media & Entertainment 1 1
Professional Services 1 1
Retail 1 3 3
Travel & Transportation 2
Wholesale Distribution & Services 5 8 1 12 1 6
Grand Total 2 3 13 41 1 69 11 2 4 86 4 41
SMART Market Feedback
WHERE - industries
Industrial Products 16% Healthcare 3%
Automotive 9% Computer Services 2%
Wholesale Distribution & Services 9% Education 2%
Chemicals & Petroleum 7% Banking 2%
Consumer Products 7% Government, Central/Federal 2%
Electronics 7% Government, State/Provincial/Local 2%
Travel & Transportation 7% Insurance 2%
Life Sciences 6% Financial Markets 1%
Retail 5% Telecommunications 1%
Media & Entertainment 5% Aerospace & Defense 0%
Energy & Utilities 4% Exclusions 0%
Professional Services 4%
Completed Engagements with Positive Outcomes
2
WHAT - outcomes
6%
Oppty
Conversion
38%
Lead
Conversion
Execution Status for Prospects
1
Task Status Custs %
Not Started 1496 80%
In Progress 71 4%
Deferred 20 1%
Canceled 106 6%
Completed 171 9%
Grand Total 1864 100%
STATUS Outcome % Total
Completed 1) Wrong Solution 3% 5
2) Client has no Budget 1% 3
3) Client has no Sign-Off/Approval 3% 5
4) Client has no compelling Need 34% 59
5) Not within current Timeframe 19% 33
6) Client with Competition 6% 10
7) Opportunity already in system 7% 13
8) New Opportunity Created 6% 10
9) Nurturing for future engagement 19% 33
Completed Total 100% 171
IMT Total
Benelux 1
DACH 95
France 14
Italy 9
SPGI 15
UKI 37
Grand Total 171
4
WHERE NEXT - Q1 prospects
WHY - patterns
3
Lead Indicator %
PTB Cloud Service Security 86%
PTB Implement Advanced Cloud Infrastructure 83%
PTB Big Data 77%
Storage 77%
PTB Cloud Computing - Virtual Environment Management 74%
Power 51%
PTB Data Center 29%
Oracle Rdbms 20%
Linux OS 20%
PTB Platform Computing 17%
HP X86 14%
Oracle Apps 14%
Oracle HW 14%
Sun Manuf 3%
Oracle Services 3%
Proportion of Customers with Positive Outcomes per Lead Indicator
On
Target
Off
Target
Healthcare 100% Banking 50%
Government, State/Provincial/Local 100% Electronics 17%
Chemicals & Petroleum 100% Wholesale Distribution & Services 0%
Retail 75% Professional Services 0%
Consumer Products 75% Life Sciences 0%
Industrial Products 71% Financial Markets 0%
Education 67% Energy & Utilities 0%
Travel & Transportation 50% Automotive 0%
Computer Services 50%
Average 52%
On
Target
Off
Target
o/w Outcome/Feedback Status for Prospects
B
Where should we
focus?
Where should we
de-focus?
What proved NOT
to be significant?
What proved to be
significant?
Where are we
engaging effectively?
Where did we
execute best?

7. Which
resource do I use?
Engage
iBS
Engage
LDRs
Engage
Mkting
Which is the BEST SALES
RESOURCE to use for a client
set?
4
Am I talking to the right PERSON at
the right ORGANISATION?
Who
do I call next?
1
Implement data-driven approach to client
selection integrated into SalesConnect.
When
do I call?
Where do I get the TIME TO
CALL and when is best to
ENGAGE?
Time
Ahead
Time
Saved
3
What
do I talk about?
What do we KNOW about client
and what’s the right TOPIC to
lead with?
Implement 360 degree view of both client
organisation and top personas
2
How do I provide my customer
with RIGHT INFO the RIGHT WAY
How
should I engage client?
Ensure targeted local market enablement to
support client cohorts.
How does ‘data-driven engagement’ change the status quo?
5