FotoSin_RBB_All

1
This document starts with a short introduction and time-path of the FotoSin project.
Document #2 until document #6 that follow show how the business idea of FotoSin
developed over time, as well as reflects on decisions that were made in the process.
#1 Introduction and time-path of the FotoSin project
#2 Winning business idea of the first round of the New Venture Competition
#3 Full business plan participating in the final round of the New Venture Competition
#4 Concrete plans in Brazil
#5 Update and progress report in Brazil
#6 A reflection on the decisions made during the FotoSin project
Document #1

2
An introduction to FotoSin
FotoSin was born during an exercise in the Monday evening Research Based Business (RBB)
opportunity recognition class by the Leiden University Prof. Harmen Jousma. The project has
grown beyond the class-room, and provided me with a 6 month full-time occupation from
August 2014 to February 2015 in Brazil.
FotoSin aimed at providing winemakers with a service that could visualize the health of their
vineyards, and therewith optimize yield and quality. The technology that enabled FotoSin to
offer this service was a spectral camera mounted on an autonomous drone.
In 2013-2014 the FotoSin was developed as part of the RBB classes, where Grada Degenaars,
Harmen Jousma and Christiaan van Gorkum have been of great help. In the framework of the
New Venture Competition a first coach in The Netherlands was Annemerie van der Burg. Later
also Patrick Davidson gave valuable feedback.
In 2014-2015 operations started in Brazil. A contract for co-development of the technology
and service with a local winemaker Lidio Carraro was signed. FotoSin was helped a lot by Tjitte
van der Werf who became a partner of FotoSin, as well as by the Dutch consulate.
The FotoSin time path
This time path puts into perspective the time at which the different documents in this report
have been published, as well as shows milestones in the progress of FotoSin.
September
2013
•Participated and won the first round of New Venture Competition with the initial business idea.
•See also document #2.
May 2014
•Third and final round of the New Venture Competition.
•See also document #3.
June 2014
•Fist prototype ready: a drone and a spectral camera to capture NDVI imagery.
August 2014
•Arrival in Brazil. Starting to do marketing anddemonstration flights while optimizing the technology for this market.
•See also document #4
Jan 2015
•First contract signed and camera prototype upgraded.
Feb 2015
•Technology transfer to partner in Brazil, return to the Netherlands.
June 2015
•Reading of The Lean Startup by Eric Ries. Reflection on the FotoSin project.
Document #1

FOTOSYN & Smart Fotosys
Fotosyn aims to develop the Smart Fotosys: a low cost
precision farming tool that will give small farmers real
time information about the health of their crops
simply by flying a drone equipped with NDVI
technology over their fields.
While good use of existing satellite NDVI technology is
reported to increase crop yields with 20% over one
year, this technology is too expensive and often
inaccessible to small framers in growing markets.
Fotosyn aims at exploiting this gap in the market by
using the steady developments in cheap and mobile
hardware to produce the Smart Fotosys.
The Smart Fotosys technology has an order of
magnitude higher spatial resolution compared to
existing satellite NDVI technology. The Smart Fotosys
will consist of smart (i.e. autonomous) and robust
hardware mounted on a drone to record time, place
(GPS) and NDVI information. It is quick and highly
flexible in monitoring difficult to access and scattered
pieces of farmland. Valuable real-time information on
crop health will be returned to the user.
Easy connectivity will allow for sending the data to
our servers for processing. With the Normalized
Difference Vegetation Index (NDVI) as basis, a secret
algorithm will be constantly optimized for different
user needs. Collecting more and more data over time
will allow for this optimization, and allow to keep
offering the best service for precision farming of
various crops.
Farmers in Southern Brazil will be the first customers
focused on. They constitute a large group of small
farmers with low accessibility to technology. Also, I
have good contacts with a senior manager that buys
crops from small farmers and sells them on the
international market in that area.
healthy unhealthy
Sattelite NDVI example
Fotosys Smartware in
a drone (impression)
Smart Photsys NDVI:
result from a prototype
NDVI principle
Contact
Jurriaan Kloek
kloekj@gmail.com
06 28934512
This example was taken as proof
of principle using a smartphone
camera and a simple infrared pass
filter. Webcam cameras are also
suitable. We can clearly
distinguish the “healthy” green
and red areas in the left picture.
Document #2

Products & Business Models
• Hardware: the Fotosys
Remotely controlled drone that can take aerial
pictures of the area swiftly and automatically, and
therewith collecting the necessary NDVI
information.
Smart Fotosys hardware may be commissioned to
be operated by a Fotosyn employee for irregular
use on an hourly basis, or leased with a long term
contract for long term use and services including
consultancy, demonstration and license to fly the
drone at any time. The hardware however always
stay property of Fotosyn.
• Online services and environment
Easy to access and easy to use online environment
(website, App, e-mail reports) that allows farmers
not only to see real time information of their
crops, but also check monthly or annual reports.
Using the online service may be paid for on a “pay
per picture” basis for irregular use, or using long
term contracts for long term use. In long term
contracts further specific user needs can be
adapted to. Contract value will be mostly
dependent on the land area for which the Smart
Photosys is used, and the user’s need for
customization.
• NDVI algorithm
The algorithm for automatically processing the
data to allow for precision farming of various
crops. While NDVI will be at its base, it may be
optimized for specific user needs and precision
farming. With a large database of information this
optimization is simplified. Acquired data will be
processes in our servers after uploading, as to
keep the algorithm secret and up to date.
Wishlist
With an automated
drone that flies
autonomously over an
indicated area at a
certain height using GPS
Photosyn can start the
leasing of the Smart
Photosys hardware.
Wishlist
With a software
developer for UI,
connectivity and
database Photosyn can
directly start offering
valuable informations to
customers, and meet
specific user needs.
Wishlist
With a senior NDVI or
precision farming
specialist from the
existing sattelite NDVI
sector, Photosyn make a
jump in the learning
curve and more quickly
adapt to different
precision farming
techniques.
Document #2

1
New Venture Round 3
Jurriaan Kloek Jurriaan@fotosin.nl
Boris Kozlov Boris@fotosin.nl
Gerben Naaktgeboren Gerben@fotosin.nl
Coach: Annemarie van der Burg
Document #3

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In short
The vision of FotoSin is that due to global population growth and (farm)-land scarcity,
agriculture will need to become more intensive and efficient. 1
Our mission is to offer a fast
and flexible precision farming solution for agribusinesses, with which they can increase their
crop yield with up to 20%. Our first product will be a drone that carries an optical system
with which the health vegetation can be easily visualized in an online environment.
Ultimately, farmers should not only use the online environment with drone and sensors that
we provide, but also share and use all the information they have available that could be of
use for increasing crop yield applying precision agriculture.
Our market research amongst others included contacting around ten farmers within our
network. We are in contact with the governmental agriculture organization Embrapa in
Brazill. This has not only resulted in finding an enthusiastic early adopters in Brazil and the
Netherlands, also we received valuable feedback. Everybody confirmed the need for a
robust and easy to use solution to perform precision farming and literature research
confirms this. While the technology can in principle be applied to all kinds of plants, we will
first focus on two niches in which we believe our competitive advantage is largest: wine
farmers in Brazil and wine farmers in the Benelux area.
FotoSin will focus firstly on the further development of the optical system, and secondly the
development of an online environment and mobile app from where farmers can see and
scroll through all the data that they acquired with our system. The drone and the software
to automatically control it using waypoints will either be bought, or supplied to us by a
partner.
Jurriaan and Boris know each other already for a long period long and well. Together they
have the technical expertise to develop the optical system and the functionality of the online
environment. While Boris is senior software developer at Elsevier Reeds, Jurriaan has
finished an international Master in physics and now is undertaking business studies for a
year. He was selected for the honors entrepreneur course of Delft, Leiden and Rotterdam
1
See also: D.K. Ray “Yield Trends Are Insufficient to Double Global Crop Production by 2050” (2013) for
a overview of the expected food demand in the world compared with food production
Document #3

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universities “Learning from Silicon Valley.” Gerben is a drone fan and expert who is new in
the team and already added value by arranging for a drone that can be used for free while
conducting our first tests. He will be mainly responsible for sales & marketing within FotoSin.
He has gained valuable experience as such during his ICT-implementation job at HC&H
consultants.
The product that we offer is such that a hybrid business model is favorable. With small
personal investment or with the right partner (Aerialtronics), a first drone with optical
system can be made operational within one month – generating the first income. While
further automating the system on the way, and by expanding the number of operational
drones, we expect that we don’t need further external investments.
FIGURE 1 – AN IMPRESSION OF A DRONE WITH
OPTICAL SYSTEM WHICH CAN BE CONTROLLED BY
SIMPLY INDICATING WAYPOINTS IN FOR INSTANCE
GOOGLE-MAPS. A FARMER DOES NOT NEED TO BE
SKILLED IN FLYING TO CONTROL THE DRONE.
FIGURE 2 – A RESULT OF OUR PROTOTYPE HOME BUILT
OPTICAL SYSTEM. THE RESULT CLEARLY DISTINGUISHES
BETWEEN HEALTHY AND UNHEALTHY LEAVES.
Document #3

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Technology
FotoSin visualized the health of crops by
combining a camera technology on a
computer controlled drone and an online
environment. This enables farmers to use
perform precision farming on their fields:
i.e. they will not optimize their field per
field, but per square meter.
The drone and the optical system that
FotoSin uses both have a robust
appearance. At first sight they will not look
less robust then a tractor as already used by
farmers. Second, an intuitive online
environment (website and app) will not only
show the results as recorded by the system
over time, but also will enable the user to
control the drone and program flights using
pre-set waypoints on for instance google
maps.
Expensive high-tech optical techniques such as multispectral cameras already have proven
their worth for the precision agriculture as well as in many other areas. By focusing on
specifically wine farmers we have developed an optical system at costs an order of
magnitude lower than an off-the-shelf multispectral camera. A proof of concept was
delivered half a year ago, currently the optical system has been integrated into a
microcomputer to allow us for automatic image acquisition control and first tests. A farmer
should be able to control this system and retrieve the data using only his mobile phone.
The first targeted application is the monitoring of vineyard health. Future applications
however are endless. By slightly modifying the optical system and optimizing it for various
applications, the technology may visualize a shortage (or surplus) of fertilizer and water. Also
specific illnesses may be shown and even soil characteristics may be determined. All those
applications of course may be optimized for different types of vegetation. See table 1 for a
FIGURE 3 – THE PRINCIPLE BEHIND THE OPTICAL
SYSTEM. WHILE BARELY VISIBLE BY THE EYE, PLANT
HEALTH MAY BE VISUALIZED WITH HIGH CONTRAST BY
COMPARING THE INFRARED AND VISUAL WAVELENGTH
BANDS OF THE SUNLIGHT REFLECTED FROM THE
LEAVES. HEALTHY LEAVES ABSORB MORE VISIBLE
LIGHT THAN UNHEALTHY LEAVES, WHILE THE
INFRARED REMAINS ALMOST CONSTANT.
Document #3

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full overview of the different techniques that are comparable to our first vineyard
application.
The software we aim to write initially will be targeted at conveniently displaying the results
as obtained by a drone measurement. Ultimately, such application may take a more generic
form keeping track of all kinds of characteristics in space and time of the farmland that are
useful to planning. An example would be the expected humidity under forecasted weather
conditions. We expect that with the experience of flying with drones and listening to our
customers, we will be able to add the right functionalities in a stepwise manner. Partnering
up with an already existing farm log provider is a serious option to make this happen quickly.
A long vision goal is to make the functionality such that farmers can easily share both drones
and data within each other via our platform as to increase crop yield everywhere.
TABLE 1: DIFFERENT APPLICATIONS OF OPTICAL FARMLAND MONITORING WITH A DRONE
Application Advantages Wavelengths
Monitoring Plant health may be monitored in detail Infrared & Visible light
Irrigation Optimizing irrigation-schemes. Infrared & Visible light
Fertilizers Optimation of fertilizer & cost reduction Infrared & Visible light
Disease Crop disease may be identified early IR, VIS & heat radiation
Soil map Mapping the nutrients in the soil Infrared & Red light
Document #3

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The management team
Jurriaan is the founder of Fotosin. He finished his Master in physics with optics specialization
in 2013. He has lived and studied in the Netherlands, Germany, France and Luxembourg. He
has been learning Portuguese for the last year, and has close ties with wine-farmers in
Southern Brazil. At this point Jurriaan is a trainee at the European Patent Office as part of
Science Based Business courses in Leiden at Leiden University. He has also been selected for
the course “Learning from Silicon Valley” between the Leiden, Delft & Rotterdam
universities – in the light of this course he will conduct a business consultancy assignment in
the area of precision farming and drones. He will ultimately aim to set up a branch of
FotoSin in Brazil.
Boris is a senior software developer at Reeds Elsevier. His background is computational
linguistics, logics and robotics. Within FotoSin Boris is responsible for software and hardware
development and integration.
Gerben is an ICT consultant with background in economics. He has a passion for flying with
drones and ways to valorize this new technology. At this moment he works four days a week
as a Consultant at HC&H Consultants. One day a week he is mainly responsible for sales and
marketing of FotoSin. His main task is to set-up the FotoSin’s branch for Western Europe.
In the table below you find a schematic overview of the skills and expertise of all the team
members.
Document #3

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Technology-Hardware
Technology-Software
Agricultureapplications
Finance
Projectmanagement
Relationships
Salesandmarketing
Production
Personellskills
Socialskills
Initiative
Communication
Salesskills
Negotiatingskills
Endurance
Jurriaan Kloek ● ● ● ● ○ ○ ● ● ● ○ ●
Boris Kozlov ● ● ● ● ● ●
Gerben
Naaktgeboren ● ● ● ○ ● ● ● ● ●
TABEL 2 – A SCHEMATIC VIEW OF THE COMPETENCES OF THE MANAGEMENT TEAM OF FOTOSIN. THE WHITE CIRCLES
INDICATED COMPETENCES THAT ARE ACTIVELY BEING IMPROVED TROUGH BOTH COURSES AND THE NEW VENTURE
COMPETITION WORKSHOPS.
Document #3

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Strategy
The hybrid business model
The development of FotoSin is based on a hybrid business model. First there will be an
innovative phase, and later a scalable phase. By piloting the product while still developing it
this summer enough income is generated to continue the R&D necessary to get to a scalable
product. See the timeline below for a good indication of the development timescales.
We focus solemnly on developing and selling the camera system and software package
around it. Those are also our main income streams. A ready to use consumer drone
compatible with our system may simply be bought, but also strategic partnerships with
drone manufacturers like Aerialtronics are actively and successfully sought.
Maximum affordable loss
By finding the right partners already during our pilot, we aim to reduce the personal
financial risk of the management team as much as possible. The worst case scenario would
be that no enthusiastic partner is found and that Gerben and Jurriaan both buy a consumer
drone to start their own Pilots in the Benelux and in Brazil respectively. After a successful
pilot case it is expected that FotoSin will be able to start selling automated system with
drones. In case of no customers the investment is no more than 5000 euro That will be no
problem for the team.
It may be noted that Aerialtronics has signed up as a partner for our test phase.
Investors
While we believe that we will be able to do everything without investors, we also realize
that the right investor can be worth a lot for our company. We are therefore looking for
investors that could potentially get into the company after the pilot phase, when scaling up
is starting to become really important. Talks are ongoing with Symbid, a crowdsourcing
investor that also seem to have some direct funds available. Using crowd sourced funding
could also increase our visibility on the market and could be considered as a marketing tool.
Document #3

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FIGURE 4– TIMELINE OF THE BUSINESS DEVELOPMENT OF FOTOSIN. ROLL-OUT MEANS STARTING WITH THE
SALE OF DRONES WITH OUR OPTICAL SYSTEM, TOGETHER WITH THE SALE OF SUBSCRIPTIONS TO OUR ONLINE
MONITORING ENVIRONMENT. AFTER THE ROLL-OUT, DEVELOPMENT WILL BE MAINLY CONSUMER GUIDED,
BUT EXPECTEDLY BE FOCUSED ON THE SOFTWARE FUNCTIONALITY.
Partners
Aerialtronics
At this point we are working closely together with Aerialtronics. Aerialtronics is an
internationally expanding The Hague based drone manufacturer. Their Altura series drones
are state of the art considering payload, flight time and performance in strong winds.
Current customers of Aerialtronics are amongst others police and fire fighting forces and
governments all over the world. They are very interested to have a local partner in precision
agriculture, mainly because they realize that selling drones for applications in this area will
become their major business over the next years.
While Aerialtronics sells a drone and its control system on a per piece basis, FotoSin remains
responsible for the camera system software package around the camera systemA successful
partnership with Aerialtronics generates a lot of credibility for FotoSin. We will also benefit
from their network and their marketing machine. On top of that we trust that we can rely on
their services and work closely together in The Hague area.
Document #3

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Aerialtronics has confirmed participation in the test flights scheduled for 9th of May at a
farm in Almkerk. Also Aerialtronics is likely to sponsor Jurriaan’s trip to Silicon Valley for the
entrepreneur course, in exchange for some business intelligence on sensors.
Southern Brazil - Embrapa
At this point in time, Jurriaan is in Brazil to strengthen ties in with local farming community.
First of all with the Embrapa agricultural organization, more specifically with the vineyard
department. Secondly with wine farmers in the regions around Porto Alegre. From this
summer onwards, Jurriaan will be there to develop the business further in this area. It is
firstly aimed to gain Embrapa (government) support to start a precision agriculture pilot
campaign in the region. If this doesn’t work out, he will look into the possibility of privately
starting such campaign and getting together cooperation of farmers to invest in a pilot.
Embrapa has reacted enthusiastically and confirmed its interest. They are now looking for
opportunities to get a visa and a salary for Jurriaan to start a pilot in Brazil.
Document #3

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Marketing
As for now, we have developed a hand-out folder to advertise our product as to convince
parties to join our pilot. By actually taking a drone on-site we will generate a lot of curiosity
towards our products and services. Also, we may find parties interested in a pilot through
Aerialtronics or Embrapa.
Once the pilots have been finished and we have results, we will advertise those results in
various ways. Think about local specialized agriculture magazines and interbranch
agriculture organizations. In the Netherlands these are the companies like Agrifirm, in Brazil
those are cooperative farmer organizations.
The price for our optical system will be competitive, a first estimate of around 3000 euro.
The price for using the software package around it will be on a subscription basis. Here we
can distinguish in pricing and functionality between a free trial version, a standard version
and a professional package. For the pilots, we will only use a standard version.
We will change our name and branding from FotoSin to something more international like
PhotoSynC or AirSpective.
Document #3

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Market, competition and our customers
Market analysis
Part of the market research was talking with farmers within our network. They were
unanimously positive and didn’t realize that the potential growth in crop yield they could
win by using precision farming techniques. Also, they inspired us with many other ideas and
applications (i.e. developing a camera system that identifies birds’ nests on grassland).
However, we have distilled the most important and will focus firstly on the monitoring of
crop health.
Farmer interviews stroke well with the findings in literature studies about the market.
Various sources confirm that precision farming is a globally fast growing market. While the
US is first with 80% of the big farmers having already adopted precision farming techniques,
still a growth of 10% for precision farming products is expected the coming years. In
emerging markets like South America penetration is not so high quite yet, but growth rates
of more than 15% are expected coming 5 years. The global market value for precision
farming will reach 3.8 billion by 2018.
The major drivers for this market are augmented crop yield & profitability, energy & cost
saving, and government assistance. Major restraints are high initial investments for users, a
lack of awareness and a high complexity.
First customers
Our first focus will be on wine farmers. This is first because of the high profit margin they
have per square meter land – while quality plays a decisive role. Second because we have
not identified any precision farming techniques currently applied on vineyards. We
therefore believe that we have the biggest competitive advantage in this niche.
By monitoring the grape quality farmers can not only increase the quality of the grapes, but
also make a distinction between normal quality grapes and high quality grapes. Price of wine
may therewith be increased correspondingly increasing yet again the profit margins. See
also the exemplary business case in the finance section.
FotoSin will be willing however, to adapt also to other niche markets when the opportunity
arises.
Document #3

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Competition analysis
Competition is divided in three major parts. First, other drone based vegetation mapping
companies. Second, alternative ways to conduct precision farming. Third, other comparable
(optical) sensors. Also the way in which FotoSin aims to maximize its competitive advantage
is described considering a certain competitor. In the table below you will see a summary of
those findings.
TABEL 3: COMPARISON OF FOTOSIN TO COMPETITOR COMPANIES
Fotosin
Sattelite
GreenSeeker
(handheld)
GreenSeeker
(tractorbased)
L'avionJaune
MijnAkker
rHydrometer
Price ++ + ++ ++ n/a +
Detail level + - ++ ++ + +/-
Terrain type ++ ++ - -- ++ -
Terrain size + ++ -- +/- + +/-
User friendly + +/- ++ + - -
Measuring time ++ ++ -- - ++ n.v.t.
Flexibility ++ -- + +/- ++ +/-
Dependent on
good weather
+/- -- ++ ++ +/- n.v.t.
Document #3

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Drone based companies
The only European based drone company we have identified is L’avion Jaune. They have
high-tech systems mounted on a drone with which they do amongst other vegetation
mapping jobs on project basis. In contrast to what FotoSin is aiming for, their jobs are always
tailor made and often for research purposes. FotoSin’s software subscription package and
drone selling strategy has the big advantage of scalability.
Alternative precision farming techniques
A lot of precision farming is done by using satellite imagery. For example NASA’s Terra
satellite holds a spectroradiometer on board which may be used to do equivalent
measurements as the optical system of FotoSin. Such imagery may be bought for 10 euros
per hectare via intermediate companies like Mijn Akker. While already operational, only few
farmers know of this opportunity because of a lack of advertisement by NASA, it is basically
a by-product for other research they are doing. Moreover, in order for satellite imagery to
work it must not be cloudy on the four days per year that the satellite flies over your exact
field and the resolution of the images is in the order of a hectare and therefore only
interesting for big farmers.
Another used technique is to actually fly small motorized aircraft with a professional infrared
photographer on board over a farmland to map a complete area. Such projects are always
tailor made for a specific application and impossible to scale up.
Big competitors on the precision farming are the products of the GreenSeeker and the like.
They have mounted analysis systems at the front of a tractor, the results of which are
directly communicated to for instance the fertilizer distribution system at the back end of
the tractor. Their system seems superior to anything FotoSin proposes because its analysis
comes with direct feedback to a fertilizer optimization mechanism. However, the technique
is unsuitable for just simply quickly monitoring the state of your fields, certainly not when
valuable crops are already growing on those fields. In any case, by focusing first on wine-
farmers we will have no troubles with the GreenSeeker.
Comparable sensors
The biggest competitor with equivalent sensors is TertraCam. TetraCam offers a camera that
allows imagery to be taken that compare to the NASA terra satellite images. This US based
Document #3

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company however seems to limit themselves only to the sensor and do not provide easy to
use software for farmers to monitor the progress of their land. Also, they seem inflexible in
tailoring their sensor to specific farmer needs and keeping their marketing focus on research
applications. Their customer and partner base is large, but mostly US based.
Unique Selling Points
The unique selling points of our technology are:
- Flexibility in space & time & application
- Easy to operate without technical knowledge.
- Scalability
Document #3

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Financial Analysis
An exemplary business case – vineyard differentiation2
Consider a standard vineyard case 1. Normally, the farmer will sell all the grapes of this acre
for the same price. Important characteristics for the different grape plants are quality and
yield per square meter. As demonstrated in case 2 in the table below, it makes still
economically sense to differentiate between high quality A and low quality B grape plants
while harvesting – the identification of which is swiftly done using our technology. The
increase in return simply by differentiating is already more than 12%.
By constantly monitoring the grapes not only may be differentiated between good quality
and between low quality, especially the low quality grapes may be doctored in such a way as
to gain higher quality. This doctoring may be done by optimizing for instance the irrigation
schemes. Case 3 shows that this may further increase the returns up to more than 20%.
Note also that extra doctoring costs have been incorporated in the harvest costs.
It may be concluded that an investment in a drone based monitoring system of 25 000
dollars drone and a 1000 dollar/year software will be profitable for a 8Ha farmer already
after three years. Note that for a 25 Ha farmer this time period reduces to only one year.
Zone
Vineyard
Area
(ha)
Yield
(t/ha)
Total
grapes
(t)
Price
per
ton ($)
Total
grape
value ($)
Harvest
costs
($)
Gross
return
($)
Gross
return
per Ha
($/Ha)
Case 1
A+B 8,47 9,7 82 1200 98400 4462 93940 11091
Case 2
A 6 6,8 41 1800 73800
B 2,47 16,6 41 900 36900
Total 8,47 110700 4800 105900 12503
Case 3
A 6 6,8 41 1800 73800
B 2,47 16,6 41 1200 49200
8,47 123000 8924 114074 13468
2
This business case was inspired by the 2004 paper “Adding value to the wine business precisely:
using precision viticulture technology in Margaret River”
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5 years of cumulative cashflow
This rough estimate of the cumulative cash flow illustrates the potential of the FotoSin
business idea in Europe. Europe has 200 million hectare of farmland. We expect only to be
able to reach 1% coming 5 years. From this 1%, only 10% is interested in buying our
technology. The average farm size is 50 hectares, leaving 4000 farmers.
We sell optical systems for 3000 euro/piece and we provide an internet service with which
at the end of the 5 years we expect to make 600 euro per user per year with income from
subscription fees and advertisements on open platform. The main costs will be employees
which will grow from 3 to 30 employees over the 5 years.
This estimate shows that the maximum valley of depth is 250.000euro, and that the
potential is more than 5 million euro over 5 years.
-1
0
1
2
3
4
5
6
0 1 2 3 4 5 6
Cumulative Cashflow FotoSin
Document #3

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Subsidies
A promising way for FotoSin to grow independently though quickly after the pilots is by
gaining subsidies. We have gained expert knowledge and there are various possibilities. A
list will follow:
- WBSO subsidy from the Dutch government that gives tax reduction for R&D salaries
- Dutch Good Growth Fund for export to upcoming markets.
- Subsidy for Food & Nutrition Delta for innovative projects in the food industry.
- Subsidy of the European Space Agency for start-ups that use space technology
(NDVI)
After the pilots we will decide upon a specific strategy regarding the different subsidies.
Document #3

FOTOSIN & RBB ASSIGNMENT
Tangible goals in Brazil
Jurriaan Kloek
Jurriaan@fotosin.nl
Abstract
In this document an overview of the planned activities of FotoSin in Brazil is presented. The
document is the first in a series documenting on the 5 month stay in Brasil. The document aims at
aiding FotoSin’s strategy and planning, as well as to meet the requirements for the RBB
assignment.
Leiden University – Faculty of Science - Research Based Business
Document #4

CONTENTS
Introduction...................................................................................................................................................................2
Technology development ..............................................................................................................................................3
Strategy......................................................................................................................................................................3
Current progress and achievements..........................................................................................................................3
Tangible goals ............................................................................................................................................................4
Regulation......................................................................................................................................................................5
Netherlands ...............................................................................................................................................................5
Brazil ..........................................................................................................................................................................5
General considerations..............................................................................................................................................5
Tangible goals ............................................................................................................................................................5
Marketing in Brazil.........................................................................................................................................................6
Current progress........................................................................................................................................................6
Tangible goals ............................................................................................................................................................7
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INTRODUCTION
The MIT 2014 technology review confirms everything what many including FotoSin believed in concerning
agriculture drones. Agriculture drones have an enormous potential to produce more food with less resources. Data-
driven agriculture, or precision farming, is a hot trend. Drones give better resolution than satellite imagery, and are
cheaper than manned aircraft. Drones are profiting enormously from advances in smartphone technology, and
therefore by sitting and waiting the technology is improving every day effortlessly. A new market is being created
and the technology to serve this market is developing at a tremendous pace.
FotoSin at this stage has successfully developed a prototype drone that can visualize crop-health, as well as
prototype software to analyze and present the data to a farmer. While the potential is great, the business reality for
starting companies like FotoSin is not straightforward. First, the stereotype of conservative farmers seems to be true
– it takes determination and effort to find the exceptions that are willing to adapt to the new technology early.
Unluckily, this seems to be especially true for artisan wine farmers even though the added value of the technology
is probably relatively high for them. Second, changing government regulations concerning drones is causing many
to be hesitant in investing. Lastly, while the hardware is not expensive for a farmer, they seem to be only interested
in the data. Merely acquiring data for a farmer however, is not a scalable business model. Those three challenges
need to be met.
While the development of the technology and product is not regionally bound, the main activities of FotoSin
marketing wise are focused in the southern state Rio Grande Do Sul of Brasil. Rio Grande Do Sul is a state with seven
times the area the Netherlands, and with a 68.000 hectares of vineyards it is the wine capital of the country. In this
report an outline of the activities planned in Brazil will be presented. First, the goals regarding improving and
producing the technology will be discussed. Second, the expected regulation developments will be assessed and
most importantly third, the planned marketing and strategy will be planned for my stay in Brazil. All this with the
insights and knowledge gained with the experiences over the last year, including a preparatory visit in Brasil and the
first few weeks here.
Figure 1 – A wine map of Brasil. The wine region is
concentrated in the South of Brasil in Rio Grande Do
Sul. The local population called gauchos originate from
Italian and German immigration in the late 19th
century.
Amongst others, they brought the skills and know-how
of the European wineries.
Picture taken from:
http://www.wineandvinesearch.com/
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TECHNOLOGY DEVELOPMENT
STRATEGY
Developing the technology has been important while producing a working prototype. The technology may be divided
in three major components: the drone, the software and the sensor system. It is striking how much the prototype
developed by FotoSin looks like the unsuccessful kickstarter project StitchCam1
. I strongly believe that at this point
the prototype is merely a marketing tool that allows to do demonstrations, and show the potential of the technology.
The strategy concerning technology development is therefore relatively reserved. Due to very high import costs, the
option of having Brazilian production must be seriously considered.
As for the drone technology, no efforts whatsoever are made to improve the performance. As stated earlier, the
developments are tremendously quick and much fueled by the advances in smartphone technology. It has never
been the ambition of FotoSin to be part of that. However, it is of great importance for FotoSin to know any recent
advances in drone technology.
As for the camera technology, I believe that FotoSin already has a home-build NDVI sensor with superior
performance compared to off-the-shelf technologies. I believe that at relatively low investment costs the camera
may be further optimized for this specific application. While doing marketing demonstrations, different optical set-
ups may be tested.
As for the software technology, a fully functional back-end prototype is ready. Increasing the performance would
require a big investment and is not considered a priority at the moment. The front-end or user-end (i.e. creating an
online environment to see the results) is not in our skillset and the investment for it is believed to be only interesting
at a later stage. This user end may be really well covered by working together with and integrating into farming
organizing software.
CURRENT PROGRESS AND ACHIEVEMENTS
I have started a buzz in three universities in Rio Grande Do Sul about drones and agriculture. I am confident that at
least one project related to drones and agriculture will roll out of those buzzes. While doing so I have come to realize
that most likely nothing technologically interesting will come out of this; I do believe however that it may help finding
out what the possibilities are to set up a production line in Brazil, something that might be a prerequisite for a
successful long-term campaign in Brazil. I will not get engaged too much in university projects, merely promote doing
drone-related things as to market the idea and keep in touch with the people involved.
Remarkably, it took me to go to the Dutch Embassy in Rio de Janeiro to be successfully introduced to the relevant
research group at Wageningen University. My tries from The Netherlands earlier have not been successful in getting
any response. I believe that potentially a very specific sensor developed at Wageningen University may be of great
value for farming applications. Certainly in research projects, Wageningen is a great partner if only to increase
1
I have been in Skype contact with the responsible of StitchCam and shared ideas and knowledge. Our prototypes
were based on the same sort of information, and therefore had a similar appearance. After a failed kickstarter
project StitchCam came to realize that selling hardware is not the way to go for this technology. Instead, a service
based business model will be the next shot of StitchCam at the Californian US market.
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credibility. In business, most likely a patent will be necessary for Wageningen to add value and credibility to FotoSin’s
business.
TANGIBLE GOALS
o Increase the camera performance by tests during demonstration flights.
o Keep in contact with the local drone enthusiasts at the universities, strengthening a network that allows for
local production possibilities in case of a long-term Brazilian campaign
o Investigate the possibilities and potential of working together with Wageningen University
o Stay in touch with and get known in the agriculture-drone world by building more relationships like the one
with StitchCam.
o Spent a week at a farmer and do measurements every day to increase
Figure 2 – FotoSin in action doing a demonstration on a
wheat field. Doing demonstrations has next to a
marketing value, also a development value. Every
demonstration FotoSin gets better at using the
technology and has new ideas for enhancing it.
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REGULATION
NETHERLANDS
In The Netherlands recent laws have been passed that prohibit the flight of drones commercially, unless tons of rules
are respected and your flight plan has gone through a bureaucratic machine. Recent cases of people being sued for
using drones inappropriately make it seem a bad idea to pursue commercial activity in the Netherlands at this
moment.
Firsthand information on the rules and regulations may be found here:
http://www.ilent.nl/Images/Informatiebulletin%20lichte%20onbemande%20luchtvaartuigen_tcm334-342963.pdf
BRAZIL
There seem to be no clear rules at the moment. Application of old law would mean that flying drones would be
illegal. However, there have been no reported cases of anybody being sued for flying a drone inappropriately. In the
contrary, Brazil is considered to be a safe-haven for drone enthusiasts worldwide due to its flexible attitude towards
drones and privacy. A local television show got famous by flying a drone up close to the window of an apartment
building and shooting images of people’s stunned reactions.
The aviation authority will most probably advice the Brazilian government to allow privately flying drones that weigh
less than 25kg up to 120 meters of altitude without restriction in the beginning of 2015. Experiments seem to be
considered as private use also. The commercial use of drones would require the operator to have some sort of a
driving license. For the agriculture-application, the drone regulation seems thus to be evolving towards a workable
set of rules in the near future.
GENERAL CONSIDERATIONS
National laws concerning drone flights are an issue for FotoSin. I would personally very much like to see European-
wide regulation. While the recent restrictive measure by for instance the Dutch government make sense taking into
considerations accidents which happened during crowded events, I am confident that ultimately the use of
agriculture-drones will be released from the regulation pressure. The current regulation has passed its goal and will
soon need to be revised.
TANGIBLE GOALS
o Keep up to date about drone regulation in Brazil/Netherlands
o Increase knowledge of drone regulation in Luxembourg, Germany, France and Belgium
o Look for joining an common interest lobby for agriculture-drones
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MARKETING IN BRAZIL
As stated in the introduction, the biggest hurdle to overcome is the marketing challenge. How to convince farmers
that using the proposed technology will add value to their day to day business? How to gain enough credibility to be
supported by major government subsidies? What price to sell the product for, and in what form? Those questions
remain unclear not only for FotoSin but also for other agriculture drone companies. In this section I will elaborate
on the marketing strategy that FotoSin will deploy the coming few months in Brazil.
Comparing to the US where large individual farmers have been using satellite imagery and manned aircraft imagery
for the last decades already and the main challenge is to provide a superior service at a lower price, the task in Brazil
seems to be different. Only the governmental agriculture agency seems to be familiar with satellite crop-health
maps. The focus therefore should be on firstly educating the farming community of the general value of aerial
imagery of their land.
Secondly, FotoSin should provide a business model that allows the farmer to use the data without scary investment
costs. This may be done by in the beginning by resorting the service based model, and slowly converting into a lease
model where the drone remains property of FotoSin while the farmer just pays a subscription fee based on the
amount of hectares monitored per month. On the other hand, it remains to be seen what will happen with the price
of drones. If drones become practically free it may be worth to sell them below cost price, and make money with
the data-processing software. Those questions will only need to be answered after there is enough interest for the
product in Brazil, but a good idea of the possibilities allows to move quickly when necessary.
Credibility is very important while making contacts in Brazil, and is mostly gained through connections. Considerable
time therefore should be spent in building a network. FotoSin has an advantage here because it is foreign and
therefore good and interesting, while also it has access to a trusted local network that can help out with Portuguese
and Brazilian customs.
While there is potential everywhere, the biggest potential for FotoSin’s technology is believed to be for wine farmers.
The size of the vineyards are about optimal for the drones currently available on the market, and the intensive nature
of vineyard management as well as the wish for high quality rather than quantity all speak in favor of using good
monitoring technology.
Ultimately, the long term goal is to see if there is a possibility to get Brazilian (government) investment into the
company, and to open a branch in Brazil. For this I believe the minimum viable product that we have at the moment
only lacks one proof of principle, and this is producing a time-series animation of one and the same field. Such an
animation, combined with one or two enthusiastic wine farmers would strengthen the story of FotoSin, ready to
speak to investors.
CURRENT PROGRESS
Unfortunately, there have as to yet not been any direct introductions to wine farmers, but only wheat farmers, soja
farmers, erva farmers (a local tea) and wine importers. To change this, we are preparing to resort to a cold calling
and cold visiting method that will be finished by the end of October. The idea is to call all the wineries in the region,
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and spend a week visiting the people and conducting presentations. Farmer fairs and the “Dutch” city ‘Nao me
Toque’ are also of special interest.
I got into contact with a group of students at the university of Caxias will be doing an entrepreneur course. After a
pitch last week I might have been able to convince them to do something with agriculture drones and even join the
entrepreneur competition: http://veja.abril.com.br/tema/premio-jovens-inspiradores. I am currently researching
the possibility of joining this competition as a foreigner. Expected gains: contacts, buzz, potential investors,
customers, know-how of the Brazilian business landscape.
One potential investor has been identified as a successful bio-diesel entrepreneur that just was bought out of his
company by Petrobras Oil Company and is looking for new opportunities. Another way to attract investors may be
to join a startup competition, or look for incubator programs. Search for investors is ongoing, talks with investors
are planned for January 2015.
TANGIBLE GOALS
o Start updating LinkedIn and Twitter once a week to increase the buzz
o Join the sailing club of Porto Alegre and look for more contacts, especially wine farmers
o Identify and join farmer fairs and do demonstrations
o Finish the list of wineries and start cold calling/visiting 50 farmers
o Do at least 7 demonstrations at wine farmers
o Build relationships with the potential customers, add them on LinkedIn/Twitter. Send them e-mail
updates.
o Find a farmer that is willing to host me for a week and allow me to do a time-series animation
o Visit the incubator program of the private university PUC in Porto Alegre, via a recommendation of an
enthusiastic prof. at the University of Passo Fundo.
o Visit the agriculture focused Dutch Consulate in Sao Paulo in November
o Consider joining the entrepreneur competition
Figure 3 – visiting an Entrepreneur fair. The textboxes
from left to right translate into:
`I am in the cloud`
`I am an entrepreneur`
`Thank you, do not send the attachment’
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FOTOSIN & RBB ASSIGNMENT
Wrapping up: how have decisions on the way
contributed to a lean startup?
Jurriaan Kloek
jurriaan@flyingfotosin.com
Abstract
After having done the RBB assignment in Brazil, I read the book “The Lean Startup” by Eric Ries.
This document reflects on how decisions that were made during the development of FotoSin in
Brazil were in line with the Lean Startup Strategy.
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TABLE OF CONTENTS
Introduction .................................................................................................................................... 2
A leap of faith.......................................................................................................................... 2
Pivot or persevere................................................................................................................... 2
The five Whys.......................................................................................................................... 3
Descisions........................................................................................................................................ 4
The start-up team ....................................................................................................................... 4
The product – a georeferenced and color-coded map............................................................... 6
Geo-refrencing........................................................................................................................ 6
Relative data or calibrated data.............................................................................................. 8
The target market ....................................................................................................................... 9
Reaching the target market .................................................................................................... 9
Big or small winemakers......................................................................................................... 9
To pay or not to pay.............................................................................................................. 10
The five whys and technology failure....................................................................................... 12
Mayday – we lost contact..................................................................................................... 12
The camera does not take pictures ...................................................................................... 13
Wrapping up ................................................................................................................................. 15
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INTRODUCTION
A LEAP OF FAITH
A leap of faith. This is how Eric Ries would have described the way FotoSin started in Brazil. Armed
with a prototype product, a business model, a value proposition and a target market – a full
fetched business plan - I booked a ticket to the Vale dos Vinhedos (The Winery valley) in Rio
Grande Do Sul, Brazil. A great idea, many assumptions – no evidence for measurable success, but
the necessary confidence that the plan that I had crafted was flawless and going to work out
perfectly.
PIVOT OR PERSEVERE
While unaware of the terminology at the time, many activities undertaken from that point
onwards have sought for validated learning – in some cases more successful than in others.
Through validated learning assumptions about the technology, market, business model and value
proposition may be tested as quickly and efficiently as possible. According to Eric Ries, efficient
validated learning is key in order to make educated decisions. You pivot or persevere only after
you know what you are doing. In other words, after you have experimental proof, you change
the initial assumptions for new ones if they are proven wrong, or persevere and optimize if earlier
assumptions are proven right.
However, many activities undertaken from that point onwards also have been characteristic from
a common trap as described by Ries. Examples are the stubbornness to stick to a plan while signs
should be picked-up that a pivot is necessary, or the ambition to achieve a certain measurable
goal, which does not contribute to efficient validated learning. In this text, there will be attention
for different decisions that have been taken regarding FotoSin, pivots that have been made and
situations in which FotoSin persevered. There will be a critical evaluation of the effect of the
different decisions on the opportunity to validate the assumptions.
This document – like the previous documents – distinguishes between marketing efforts as well
as product characteristics. Next to that, crucial decisions have been made in an effort to build the
right team around FotoSin in Brazil. All those will be discussed in terms of pivoting or persevering
with or without validated learning.
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THE FIVE WHYS
A good mechanism to deal with emergencies, unexpected errors and other problems is presented
by Eric Ries as the Five Whys. Whenever an error occurred, you ask in a baby-like fashion why
that error occurred to get to the root cause of the error. This line of thinking allows to react
adequately to the error without underinvesting nor overinvesting in appropriate solutions.
Within the five whys framework, it is ok to have a certain mistake or error occurring, but then
the organization should learn and adapt appropriately in order to have it never happen again.
The Five Whys help a start-up to quickly get to the root cause of a problem, while finding
appropriate solutions at all levels of the organization.
I believe that FotoSin has automatically adapted this strategy to solve emergency problems, and
two examples will be given in terms of technology failure.
Figure 1 – a map of Brazil and the different winemaking regions. The most famous is The Vale
Dos Vinhedos, which is inside the Serra Gaucha, in Rio Grande Do Sul. I was living in the capital
of the state, Porto Alegre.
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DESCISIONS
THE START-UP TEAM
I realized that there was no way that I could pull-off FotoSin off alone in a country with a different
(business) culture, with a language that I hardly speak and without network. In the ideal case, I
would set-up a cell of FotoSin in Brazil in half a year, by educating locals about the technology
and the value proposition. This cell would then be able to operate independently which allowed
me to proof the concept. With the proof of concept, I could look for investments in order to setup
cells in different places around the world. While this idea of building a team was never written
down nor spoken out concretely, looking back it surely was part of the initial strategy.
The initial idea was that I needed a team of young (English-speaking) university graduates with
some technical affinity, whom would get enthusiastic and would pull off most of the operations
of the project in exchange for the experience of being able to do an internship. The promise was
that after a successful internship, they could become stakeholder in the company if successful
and they stayed. At the same time, I needed a heavyweight partner for strategic planning and
formalizing business deals. For the latter I found - via the Dutch consulate - a senior international
business development consultant with Dutch roots whom was enthusiastic about FotoSin and
would later become my partner.
For the former, I visited different universities as well as an entrepreneurship event in order to
pitch my idea and increase my network. Indeed, I got contacts of at least two students looking
for internship possibilities, as well as a PhD that was involved in remote sensing. A group of
entrepreneur students used my business case in their “opportunity seeking” class. For some time
I had hope that a tax law consultant between jobs and looking for a new opportunity would be
interested in helping with getting government support in forms of tax benefits and subsidies.
However, in the end none of them would engage in a more formalized and active role within
FotoSin and its operations.
During one of the lunch meetings with my partner, I discussed with him my frustration that I
could not find a young entrepreneur who would want to assist me with flying the drone and deal
with customers: the operational part. He mentioned that he would be willing to take this role
upon himself. While I was skeptical about his technical affinity at first (I would have to teach him
how to control the drone with an IPad, while he never used a touchscreen in his life), I pivoted
after three months of fruitless recruitment efforts, and started teaching him how to use the
drone. This decision arose more out of panic than out of a strategic decision making mechanism
– after all, I needed someone to continue operations after I returned to The Netherlands.
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The lesson learned is that the stakeholder promise to students is not necessarily a very strong
one (also in the Netherlands I did not manage to motivate fellow students with this promise). I
never asked, but I suspect that the most direct cause for the reluctance to join is the lack of direct
remuneration. Next to that, I assume that students in the Netherlands are looking for
professional coaching and a company that is strong for CV building.
In this case, I clearly missed a chance for more validated learning. If I had asked everybody who
was initially interested why they were not joining in the end, I could have drawn harder
conclusions and maybe pivoted earlier. I could have found ways for professional mentoring to
make the offer more interesting, or realized that the target-group of university graduates was
the wrong target-group. Maybe the direct family of the winemakers themselves would have been
a great target group, as many businesses have a strong family ownership. Those assumptions
would certainly been worthwhile testing, and could have gained me insightful information for
shaping the business the right way in the future.
Figure 2 – My partner in action with the drone.
While he was a great business developer with
a great network in the region, it cost a serious
effort to teach him how to operate the drone
independently, which was not completely
efficient.
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THE PRODUCT – A GEOREFERENCED AND COLOR-CODED MAP
For FotoSin I believed that by using the camera and drone technology, we could offer a map to
winemakers that would allow for precision agriculture: the vineyards could be monitored and
optimized per square meter rather than per block. I had two key features in mind:
1. Relative NDVI data that distinguishes between good quality grapes and bad quality
grapes.
2. Geo-referenced pictures. (I.e. the customer would be allowed to look at the map on an
IPad, and then use the GPS of the IPad to see where actually you were walking inside the
map, an experience equal to the service of google satellite).
Figure 3 – The initial product. A color-coded
and georeferenced map overlay on Google
Satellite of some Dutch grass fields. A
difference is clearly seen between the colors of
vegetation (yellow-red) and the canals
(green). This color-coding is not calibrated and
only gives relative data. With the geo-
referencing, a farmer could treat every square
meter of his land according to the insights of
the color-map.
GEO-REFRENCING
After having presented the technology to different winemakers, the winemakers never really
reacted noticeably to the geo-referencing feature. I realized that this geo-referencing was an
unnecessary feature after I did a flight after which I had no time to actually do the geo-referencing
before presenting the data in the next meeting. My gut feeling already told me that this was not
a huge problem, and I presented the non-georeferenced data without mentioning the inferior
features of the data. Indeed, no questions were asked whatsoever.
The winemakers do not care about geo-referencing because their vineyards are referenced in
their own reference systems as may become apparent by looking at Figure 4. From the moment
that I realized this on, I saved a lot of time (one or two days of data crunching per map in order
to get the maps geo-referenced) by simply deleting this feature.
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I clearly made a wrong assumption about the customer need, and added an unnecessary feature.
I could have saved a couple of weeks of development efforts if I had never started with geo-
referencing in the first place, and first asked the customer about the need. Alternatively, I could
have introduced only a very rough and quick version of geo-referenced data and observed the
reaction of the winemaker. If the winemaker would have been indifferent, I would not spent
more time and forget about the feature. If the winemaker would have said: “wow, geo-
referencing is a really nice feature, if only it could be more precise.” I could have increased efforts
in making a very precise geo-referenced map. While the process of validated learning could have
been quicker, I am proud to say that I recognized the discrepancy between my assumptions and
the actual needs, and acted accordingly.
Figure 4 – A false-color NDVI map of a vineyard. Geo-referencing is unnecessary because the
vineyard has its own reference system. Every block had its own letter-code. In every block, rows
can be distinguished which each have a certain number code. In every row, vines are planted
on regular intervals, which again have number codes. From left to right, the rows 1 until 19 in
block A for instance, show different NDVI characteristics than its neighbors. The maps of FotoSin
with a pixel resolution of about 5cm, can distinguish between subsequent plants as well as rows,
and therefore a separate geo-referencing feature is irrelevant.
B
A
C D
0 10 20
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RELATIVE DATA OR CALIBRATED DATA
By calibrating the NDVI data we would allow for the comparison in time of subsequent NDVI color
maps. A farmer would be enabled to compare NDVI results from month to month, and even from
year to year. Eventually, the effect of certain actions (different irrigation, pesticide use or
fertilization methods) could be measured.
I am still in doubt with the need for calibration. My initial assumption was that calibration is not
relevant; it is important to be able to distinguish between good quality grapes and bad quality
grapes without a necessity of absolute measures. Water management and the timing of harvest
may then be optimized simply by trying to change the parameters such that the lower quality
grapes increase in their quality.
In addition and more importantly, I realized that a wrong calibration and therefore a wrong
interpretation could potentially do a lot more harm than simply looking at differences. Calibration
is extremely difficult and work intensive. First because the atmospheric conditions may change
from day to day – even hour-to-hour, changing the received spectrum and therefore the NDVI
values. Second because the NDVI characteristic of vineyards are related to the different
maturation stages of the grapes. Calibration therefore needs to be done often and interpreted
very carefully in order to yield good results, much complicating the operations.
Even with all my concerns and arguments, our most important customer would really love to
have calibrated maps, in order to compare maps year after year after year. Until now, I have not
honored this request because I only heard it from this one winemaker. Calibration does not seem
to be an issue for the others. On the other hand, it feels like a failure not to deliver the request
of one of the bigger and most promising customers.
To solve this issue in the future, a quick experiment needs to be designed in order to definitely
make a decision about the feature of calibration. Does all the extra-work during operations
outweigh the benefits of the customer? Clearly, this case requires an experiment that can proof
the assumption right or wrong, without first developing a fully functional calibration method.
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THE TARGET MARKET
REACHING THE TARGET MARKET
My initial assumption was that through my connections in the sailing club, Dutch consulate,
university, research institutions etc. Someone would automatically introduce me to a winemaker
in my increasingly larger network. This was a wrong assumption and an inefficient method.
After 2 months without having reached a winemaker (but many other types of interested farmers
that were not my target market, see also picture 5), I realized that I had to pivot and change my
strategy. I resorted to cold calling a list of winemakers in the Vale dos Vinhedos that I had
retrieved through the tourist information office, starting with the smaller ones.
Picture 5 – FotoSin doing a flight on a
rapeseed field. Through my network, I was
introduced to many types of farmers, but not
winemakers. While everybody was
enthusiastic, FotoSin had no value proposition
for other than winemakers ready, and
therefore those visits were not very effective.
BIG OR SMALL WINEMAKERS
My initial assumption was that FotoSin should focus on small winemakers. On a day of doing
flights, the technology of FotoSin could cover a maximum of 50 hectares of vineyards. The bigger
winemakers had often more than 500 hectares of land, while the smaller ones had a minimum
of 10 hectares.
However, soon I realized that the smaller winemakers were not interested in such technology.
They mostly said that they valued a lot the traditional way of winemaking: they wanted to defend
their artisanship. Other excuses I heard were a lack of funds for such investment. In the end, I
managed to have an open conversation with one small winemaker, who mentioned that on a
field of 20 hectares, an artesian winemaker could easily have up to twenty different grape
families. I never realized this before, and greatly undermined our concept of relative data for the
small winemakers. After all, it would not be possible to compare the values of two different types
of vines, and 1 hectare would be a too small area to look for vineyard variability.
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After only a few days after the cold-calling campaign, I realized that I had to shift my focus to the
bigger winemaker brands. Those would often employ special quality engineers that were
responsible for the quality of the different grapes by using all sorts of data-driven experiments.
The bigger winemakers could have up to 20 different grapes, but distributed over 500 hectares
that would allow for a good vineyard variability analysis. In this case, we did not only rely on cold
calling, but also simply visiting the headquarters and asking for information (often guided tours
were available and by asking the right questions we would soon have an appointment with the
appropriate engineer). We managed to talk to and do demonstrations for four engineers of four
different companies, where there are only six or seven bigger wineries in the region.
Figure 6 – FotoSin closes its first deal for a
pilot project. Lidio Carraro is a relatively big –
but family owned – winemaker. The father
started the business, but the sons are taking
over. One of the sons married the wine-
engineer Monica Rossetti, who has adopted a
very data-driven approach to high quality
winemaking. Their quality driven approach
combined with good marketing, made them
produce the official Fifa World Cup 2014
wines.
TO PAY OR NOT TO PAY
To understand this section you must realize that the person to convince was first the winemaker:
the engineer that is responsible for the quality and the yield of the grapes. Second, this
winemaker would have to convince the management of the company.
All of the winemakers in the bigger businesses were interested, and one winemaker convinced
her management to invest in a pilot campaign already this year, see also Figure 6. The others had
no budget this year to invest in a pilot project, but most probably would like to participate the
next season. At the time, I was convinced that I had to have paying customers and therefore I
stopped working with them. I wanted paid customers because the financial transaction would
show later investors that there was a real interest in the product.
With hindsight, I believe I missed a chance by not offering the pilot for free, in exchange for
feedback on the results. This feedback would have been invaluable for further development of
the product. Eric Ries does not completely agree with this, and claims indeed that you get the
most valuable information only from committed paying customers. I believe that in this case the
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commitment for giving thorough feedback already could have been enough investment from the
customer side.
The bottom line is that I did not base my decision not to work with them in order to get more or
less feedback on the product, but because I wanted to have only paying customers in order to
show a potential investor the real potential of the product. With hindsight, I believe that the
ambition of getting paid customers was a faulty one, and that I could have learned a lot more
about the product (i.e. calibration yes or no?) if I had not insisted so much on immediately being
paid. Especially in the case of one winemaker that had an ongoing collaboration with a
winemaking research institute that I also had already established contacts with.
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THE FIVE WHYS AND TECHNOLOGY FAILURE
The five whys is a great mechanism to resolve issues concerning technological failure efficiently
without overinvesting nor underinvesting. Consider the example of a car manufacturer that is
getting feedback about a failure in the electric window control mechanism. With overinvesting is
meant that you do not need to replace all the cars completely, and start a complete new R&D
program focused on the window opening mechanism. With underinvesting is meant that it is
probably not enough effort to just replace all the defect windows, without asking yourself why
they are defect in the first place. While I have adopted this strategy almost spontaneously, Eric
Ries explains theoretically, why and how this is so important. With two examples, I would like to
demonstrate how the five whys have helped me dealing with unexpected situations, and invested
time and resources appropriately. Basically the five whys concept is nothing more than forcing a
team to use their common sense, instead of overreacting in emotions or blaming each other.
MAYDAY – WE LOST CONTACT
In one situation, I was doing a demonstration for a university. While the drone was flying its
preset route, I lost complete contact. The drone never returned, and we were afraid that in the
worst case it could have crashed in a nearby lake. The five whys allowed me not only to retrieve
the drone, but also to avoid a similar situation or worse in the future. Consider the following
sequence of questions and answers:
1. Why did the drone not return? Probably because it finished its preset route, did not get
any new order because it lost connection. It ran out of battery and then made an
emergency landing with the last little bit of energy landing. In order to retrieve the drone
we should just go and look at the location that was the end-point in the preset route.
2. Why did the drone lose contact? Probably because the antenna of the ground-station was
behind a pile of sand of an ongoing construction project, and therefore not anymore in
the line of sight with the drone.
3. So even with losing contact, why did the drone land 500m away from its take-off point?
Because it was pre-programmed to end its journey there.
In this case, the root of the problem already is reached after only two or three whys, and the
remedy was relatively simple. It certainly did not require buying a new drone with better
specifications. We indeed retrieved the drone at the end of the pre-programmed route, and the
ad-hoc problem was solved (1). After this experience, we always made sure to put the antenna
of the ground station on an elevated position, in order to be ensured of a maximum line of sight
(2). For all future flights, we also pre-programmed the drone such that the end-point would
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always be close to the starting point, so that if anything goes wrong, it would always land close
from us (3). Next to that, it became a standard practice to make sure that if the drone would have
to pass over water during flight, it would do so in the beginning of the flight in order to ensure
enough battery power and avoid an emergency landing in the lake (bonus).
THE CAMERA DOES NOT TAKE PICTURES
Initially I developed a RaspberryPi based camera. The RaspberriPi platform with its small yet
powerful processor allows for relatively easy and flexible prototyping of a wide range of technical
product at a low price. My prototype required external batteries to power-up the RaspberryPi, a
laptop with a LAN-cable to start the raspberry pi before take-off, as well as very good timing
because once the RaspberryPi was programmed to take a series of pictures, there was no way
back. More often than not, something went wrong and after the flight I realized that none or only
part of the photos were taken.
1. Why the camera was not taking pictures? The external battery might not be delivering
enough power.
2. Why the camera was still not taking pictures? Inflight vibrations might cause the
connection between the RaspberryPi and the external battery to fail.
3. Why does the camera still stop taking pictures halfway its flight? The temperature
difference in-air might change the output power of the battery, as well as the amount of
pictures being taken is simply too high.
4. Why are we using such a vulnerable system for the camera? The RaspberryPi allows for a
lot of customization, and at the same time is cheap yet still good enough for
demonstrations and tests. However, for actual work a more solid solution is needed.
Only after four whys enough questions were answered. As long as FotoSin was only doing
demonstration flights and test flights, there was no problem for failure of the camera. Nobody
would notice anyway and every time we could try to find low-cost solutions for the problem. I.e.
use a different battery (1), use extra tape to connect the battery to the RaspberryPi (2), optimize
the amount of pictures being taken with the flight speed in order to safe battery (3). However,
when we were close to closing the first deal and we were actually required to perform on the
spot, a solid solution was needed. I ordered a GoPro camera and modified it for NDVI purposes.
The easy to use and reliable GoPro camera never showed any of the above problems, and an
investment was done exactly on the right moment (4).
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The GoPro camera arrived two days before we scheduled our first commercial flight. Todayt is
still in use with my partner in Brazil and because is so easy to operate and reliable, we never had
any issues again with taking pictures.
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WRAPPING UP
All with all The Lean Startup by Eric Ries provides an interesting framework to reflect on decisions
made during the FotoSin campaign. However, this reflection must be placed in a context in which
the data driven approach with validated learning through short experimental cycles as advocated
by Ries, is not so easy when distances for conducting one experiment are averaging 250
kilometers per customer – a reality that needs to be generally faced in Brazil. Why are distances
250 kilometers per customer? Because circumstances made me live in the capital of Rio Grande
Do Sul, and not directly in the Vale Dos Vinhedos. Why circumstances did not allow me to live
directly in the Vale dos Vinhedos? Because my Portuguese classes were in the capital, and anyway
there was nothing in the Vale dos Vinhedos apart from wineries. Why did you need Portuguese
classes and something more than just wineries around you? Well…
As far as building the team is concerned, a more active approach to finding the roots of the reason
for nobody joining the start-up team would have allowed FotoSin to develop a better proposition
for future employees, and therewith to develop a superior strategy for growing the team.
Actually, looking back, some kind of unconscious strategy of what the startup team should look
like was present, but this was never formalized in a written strategy. Why was this never
formalized? Maybe because I did not have the right skills to see this at that point in time. Why
did I not have the right skills? Maybe because I am too young and unexperienced. Why did I
decide to pull of this project while being young and unexperienced? Well…
As far as the end product is concerned, Eric Ries believes that with more experimental data and
shorter prototype cycle times, FotoSin would have collected more valuable information for
creating a successful business model. This could have been achieved with less focus on paying
customers, and more focus on validated learning.
As for the target market, I believe that FotoSin has relatively quickly pivoted towards the right
customer segment for its product within the context of the Brazilian winemaking industry. Initial
assumptions were relatively easily falsified and new insights were gained. In the future, it remains
to be seen if there are customer segments with still higher added value in other wine regions. An
example could be Chile, where the wineries are relatively advanced and data driven.
The framework of the five whys forces teams to think with common sense and logically, without
blaming each other and to get to the root of the problem, and without overinvesting in an
emotional reaction nor underinvesting in order to deny the root cause of the problem. In the
context of FotoSin I feel that this common sense was always intrinsically present, and we have
never had never any problem is solving such emergencies. As I tried to illustrate in the first two
paragraphs of this chapter, the five whys are not useful to solve every problem efficiently.
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