Troels Hessner, Partner, Forecast.it

1. www.forecast.it 12015 © Copyright Forecast.it A/S
Partnering with:Troels Hessner
Partner, Sales & Business Development
th@forecast.it
Jan. 28th 2015

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About Forecast.it
• Startup based in Copenhagen
• Founded in 2011
• All-in-one Project and Por/olio Management Solu1on

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Customer pain
• Nearly one half of so4ware projects (44%) are
unsuccessful
• 11% of all so4ware development investments are lost
56%
44% Successful
Failure
*Source:PMIPulse2014(http://www.pmi.org)&CIO.com

4. www.forecast.it 42015 © Copyright Forecast.it A/S
Where we provide most value
Your organizaonal status?
Op1mizing
Managed
Integrated
Consistent
Ini1alProcess uncontrolled, no 1me
registra1on, unpredictable
cost/schedule/quality, reac1ve
and individually driven
Some processes documented for projects,
varying cost/quality/schedule, reac1ve
Processes documented for organiza1on,
reliable cost/schedule, proac1ve
Quan1ta1ve control, KPI’s, well-
de@ned process, uniform success
Con1nuous improvement, success is norm,
data-driven, automated, cost/schedule
improving

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Typical problems
• Low project pro@tability and predictability due to
inaccurate planning
– Cost overruns are common
• Quotes and proposals are generated using spreadsheets
– These tools are typically not very intelligent or well integrated to
corporate @nancial and opera1onal systems
• Lack of intelligence and integra1on into back-end
systems
– No data visibility, synchroniza1on, and accuracy which can
signi@cantly erode pro@t margins
– No early warnings for projects going oC track

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Typical esmaon approaches
• 3-point
• PERT
• Ac1vity breakdown
• Story points
• Use Case Points
• Func1on Points
• COCOMO I/II
• Other costs
• Combina1on

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Process quality maers
• If we are not disciplined about the way we develop
so4ware and collect data we will never achieve
dependable and consistent results
• This is valid for the en1re end-2-end IT project process
– Not just development and test

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Improving the process
• Data is your best weapon to ensure predictability
• There is no direct rela1on between predictability and
detailed es1ma1on
• It is what you don’t know you don’t know that creates
the largest problems in terms of lead 1me variability
– Structured data can help you with this

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Collecng and measuring data
• It's not that important what the sizing unit of data is
collected as:
– E.g. points, t-shirts, ideal hours, dogs
• The importance comes from:
– Picking a scale and s1cking to it in the long run (do
not suddenly switch from points to t-shirts)
– Correla1ng the actual amount of work with the
sizing unit, so we can learn
– Not storing the data in a PM's head

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T-shirt size distribuon behaviour

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Price per point distribuon

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Agile vs. tradional projects
• Both approaches have their bene@ts and drawbacks
– Don't make it a war about religion
– Choose the methodology (or combina1on) that suits
your organiza1onal temper
– It's not that important for ensuring predictability
●
Data is important!
• We use agile (Scrum with Kanban) for some projects
and a more tradi1onal Waterfall type approach for
others

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Pro-acvely learn from your projects
• Collec1ng data in a structured manner from your
projects enables learning that can be used extensively
– For example it is possible to obtain up to 95%
accuracy using only small, medium, large es1mates
for user stories
– Es1ma1ng becomes 2nd
nature and will not require
heavy amounts of work
– Inexperienced PM's, developers etc. will s1ll be able
to es1mate accurately

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• Problem
●
No uniform process
●
Manual handling of es1mates and no re-use of data
●
Closing the gap between pricing and delivery - Examples of
projects going extensively over 1me and budget
• Solu
on
●
Op1miza1on and standardiza1on of the es1ma1on process
●
Ensuring that data is centrally collected in a structured manner
●
Use metrics they are familiar with (3-point Func1on Points)
Case: Nets

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Our approach with Nets
• Forget the details
– Pure ”top-down” approach
– We can always make the data more granular
• Solu1on support instantly
– No need for heavy process implementa1on
• Timeboxed implementa1on
– Weeks, not years!
– Con1nuous, incremental re@nement of data and process a4er
implementa1on

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Nets project model – PRINCE2 with Scrum

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• Be
er predictability – Es1mates are generated from actual
performance
• Visibility and key insights – Automa1c collec1on of analy1cs
and insights across projects in the organiza1on creates
transparency
• Increase in project performance – Algorithm in Forecast.it
enables and drives con1nuous and automa1c feedback on
performance
• Reduce administra
on – Op1miza1on and standardiza1on of
the es1ma1on, priori1za1on and execu1on process minimizes
administra1on and manual re-work
Bene0ts for Nets

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Client case
“Forecast.it has enabled me to get rid of troublesome Excel
spreadsheets. With the Forecast.it soluon I can quickly nd
the data I need. Our esmates have improved signicantly.
It is extremely simple to use.”
Michael Bøje Andersen, Nets
LargestNordicPaymentProvider
Proven ROI of 2,2 mio.
USD in less than 3 years

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QA
Nets has executed around 330.000 project hours esmated
through Forecast.it with an accuracy of 94.4%
Ques1ons?
Nets has executed over 330.000 project hours esmated
through Forecast.it with an accuracy of more than 90%
An improvement of at least 12 pts. from their previous
soluon

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Contact
Thank you for your 1me!
info@forecast.it
+45 6177 9722