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www.forecast.it 12015 © Copyright Forecast.it A/S

Partnering with:Troels Hessner

Partner, Sales & Business Development

[email protected]

Jan. 28th 2015


About Forecast.it

• Startup based in Copenhagen

• Founded in 2011

• All-in-one Project and Por/olio Management Solu1on


Customer pain

• Nearly one half of so4ware projects (44%) are

unsuccessful

• 11% of all so4ware development investments are lost

56%

44% SuccessfulFailure

*Source: PMI Pulse 2014 (http://www.pmi.org) & CIO.com

http://www.pmi.org/


Where we provide most value

Your organiza�onal 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


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


Typical es�ma�on approaches

• 3-point

• PERT

• Ac1vity breakdown

• Story points

• Use Case Points

• Func1on Points

• COCOMO I/II

• Other costs

• Combina1on


Process quality ma"ers

• 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


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


Collec�ng 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


T-shirt size distribu�on behaviour


Price per point distribu�on


Agile vs. tradi�onal 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


Pro-ac�vely 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


• 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

• Soluon

● 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


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


Nets project model – PRINCE2 with Scrum


• 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 administraon – Op1miza1on and standardiza1on of

the es1ma1on, priori1za1on and execu1on process minimizes

administra1on and manual re-work

Bene0ts for Nets


Client case

“Forecast.it has enabled me to get rid of troublesome Excel

spreadsheets. With the Forecast.it solu�on I can quickly �nd

the data I need. Our es�mates have improved signi�cantly.

It is extremely simple to use.”

Michael Bøje Andersen, Nets

Largest Nordic Payment Provider

Proven ROI of 2,2 mio.

USD in less than 3 years


Q&A

Nets has executed around 330.000 project hours es�mated

through Forecast.it with an accuracy of 94.4%

Ques1ons?

Nets has executed over 330.000 project hours es�mated

through Forecast.it with an accuracy of more than 90%

An improvement of at least 12 pts. from their previous

solu�on


Contact

Thank you for your 1me!

[email protected]

+45 6177 9722

mailto:[email protected]

Education

Benyt fortiden til at spå om fremtiden v/Troels Hessner