Twice a year, TriFinance launches its IM Barometer. This slideshow will guide you through the results.

1. BAROMETER SURVEY & DATA
INSIGHTS
Event for Interim Managers
7 mei 2014
1

2. Agenda
• Introduction
• Freelance Barometer
– The freelancer
– The market
– Service Providers
– Once a freelancer, always a freelancer?
• From data 2 insights
7 mei 2014
2

3. FREELANCE BAROMETER
Insights april 2014
7 mei 2014
3

4. 7 mei 2014
5
The freelancer

5. Our definition of a freelancer
7 mei 2014
6
We define a freelancer as an
interim manager, or expert
working on a temporary and
independent basis with a
company or organization.

6. Freelance Barometer 2014
7 mei 2014
7
84% 16%
300
respondents

7. Age & Seniority
8
Age Seniority
N = 271
0%
5%
10%
15%
20%
25%
25-29 30-34 35-39 40-44 45-49 50-54 55-59 60+
2012 2013 - H1 2013 - H2
0%
5%
10%
15%
20%
25%
30%
<1 1-2 3-4 5-7 8-10 10+
2012 2013 - H1 2013 - H2

8. Main activity domains
9
N = 407
ICT
Marketing &
Communication
Finance & Accounting
HR & Training
Procurement, Supply chain
& Logistics
Operations:
production, manufacturing
& quality
Legal
Sales
R&D and engineering
Administration
Customer Services
Project Management
Other
2013 - H2

9. Industries you operated in over the last year
10
N = 461
(Fast moving)
Consumer goods and
retail
Public
Non Profit
Education
Tourism & Horeca
Automotive, Transpo
rt & Logistics
Finance, Banking &
Insurance
Healthcare
IT & Telecom
Creative, Art, culture
& photography
Media

10. Regions you are currently working in
11
88
18%
23
5%65
13%
36
7%
23
5%
9
2% 6
1%
23
5%
1
0%
162
32%
26
5%
Abroad: 39
7%
N = 501

11. 7 mei 2014
12
The market

12. Chargeability at the moment
13
N = 277
Yes:
(2012:
71%)
80%
13%
1%
6%
20%
I don't find an
assignment
It is my choice not to
have one
Other
Yes: No:
(2013 – H1: 83%)
(2013 – H1: 17%)

13. Finding your last assignments was…
14
0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%
More difficult
to find an
assignment
Stayed stable
A bit easier to
find an
assignment
A lot easier to
find an
assignment
2014 - H1 2013 - H2
N = 278

14. (Average) fee evolution
16
N = 278 (2014)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2010 2011 2012 2013 - H1 2013 - H2 2013 - H2 -
expected
Increased a lot
Increased a bit
Remains stable
Dececreased a bit
Decreased a lot

15. Expected fee vs Real fee
17
N = 278 (2014)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2012 -
expected for
2013 - H1
2013 - H1 - real
fee evolution
2013 - H1 -
expected for
2013 - H2
2013 - H2 - real
fee evolution
2013 - H2 -
expected for
2014 - H1
Increased a lot
Increased a bit
Remains stable
Dececreased a bit
Decreased a lot

16. Average Fees
18
N = 274
0%
10%
20%
30%
40%
50%
60%
< 500 500-700 700-900 >900
2013 - H2

17. Average duration projects
19
N = 278
0%
10%
20%
30%
40%
50%
60%
70%
80%
0-3 months 4-6 months >6 months
2012 2013 - H1 2013 - H2

18. Expected competition evolution
20
N = 284
1%
4%
40%
29%
26%
0%
5%
35%
39%
19%
0%
6%
40%
38%
15%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
Decreasing a lot Decreasing a bit Remains stable Increasing a bit Increasing a lot
2012 - expected for 2013 - H1
2013 - H1 - expected for 2013 - H2
2013 - H2 - expected for 2014 - H1

19. 7 mei 2014
22
Service
providers

20. How did you find your assignment?
23
N = 361
4%
37%
38%
7%
15%
2013 - H1
4%
42%
37%
7%
11%
2013 - H2

21. Service providers – How Many?
24
N = 131
0%
5%
10%
15%
20%
25%
30%
0 1 2 3 4-5 6-10 10+
2013 - H1
2013 - H2

22. Service providers – Succes Rate
25
N = 131
0% 20% 40% 60% 80% 100%
0
1
2
3
4-5
6-10
10+
2013 - H2
2013 - H1

23. 7 mei 2014
26
Once a freelancer
always a freelancer?

24. Do you want to stay a freelancer?
27
N = 277
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
2012 2013 - H1 2013 - H2
I want to go to a payroll job I don't know I will stay a freelancer

25. Reasons to stay a freelancer?
28

26. Reasons to choose for payroll?
29

27. Event for Interim Managers
TRIFINANCE BELGIUM
29 APRIL 2014
Jean-Marie Bequevort

28. Over 40% of the companies that were at the top of the Fortune 500 in
2000 were no longer there in 2010 (Brian Solis, Future of business)

29. Business
landscape
Technology everywhere
Digital behaviour
Explosion of data
Speed of action
New business models
Constant flow of changes ...

30. Big data: a simple concept
…
Big Data
Velocity
VarietyVolume

31. … with large impact
Ability to analyze how things
interact in extremely large data
sets, with the goal to provide
management with a clear
problem diagnostic, facilitate the
detection of opportunities and
make sure organisations are fit for
today’s business landscape
So what?
Who cares?
Why you?

32. Upgrade finance to next
impact level
1
2
3
Business
partnering
Process
improvement
Risk
management
Typical questions
• Which are the best prospects to focus on?
• How do we best spend our marketing €?
• Why are sales reps successful?
• How much time do we lose on low value-
added tasks?
• Should we harmonize and centralize
tasks?
• Which bottlenecks cause which delays?
• Are we sure there is no fraud?
• What are the leading attributes for project
failures?
• Do we always comply to our policies?
3 areas of clear quick wins

33. Business partnering: connect with growth
Micro-market opportunities
(Distribution coverage)
Optimize product mix
(Retail shops)
o Find statistically relevant combinations of
products in very large data sets
o Detect patterns of buying behaviour in
your client data
o Experiment, measure and learn ... at
scale (marketing campaigns)
o Use open data to see how your business
will fit in the future
o Map the markets to detect micro-
opportunities of growth based on key
attributes (age, gender, income, etc.)
o Use interactive visuals to engage the
front-line team to action

34. X-ray your processes
(Financial close, P2P, trading,...)
…and focus on the real issues
Discover: what is happening?
Conform: does this conform/comply to what
should be happening?
Enhance: show throughput time,
effectiveness, rework, bottlenecks, dead
ends, etc.
o Look for behavioural patterns and root-
causes by drilling down into variants
o Use these detailed insights to optimize
efficiency, effectiveness, agility and
compliance
o Identify best practices and drive
harmonization across processes
Process improvement: mine for agility

35. Fraud detection
(Claims request in insurance)
Audit & compliance
(Purchase orders authorisation)
o Find claim patterns in the claim history,
client and policy data that would
indicate possible fraud
o Identify potential key attributes leading
to fraud exposure using large scale
network analytics
o Run models periodically on those risk
attributes on all data, not just samples
o Find irregularities in approval flow
Risk management: control beyond limits

36. Accelerate the pace of
adoption
Educate Explore Engage Execute
Gather
knowledge and
observe the
market
Develop a
roadmap based
on business
needs/challenge
s
Pilot big data
initiatives to
validate value
Deploy more
initiatives and
continue to
extend
advanced
analytics
~24% of
respondents
~47% of
respondents
~22% of
respondents
~7% of
respondents
Finance should play a leading role in any “big data” mindset
transformation
Source : Survey from IBM Institute for Business Value and the Saïd Business School at the University of
Oxford

37. Jean-Marie.Bequevort@trifinance.be
@Bequevort
Everyone starts to have faith in technology …
Let’s stay in touch