Meet our new country representative for Indonesia - Tri Padukan Purba or Dukan

Photo_Dukan2.jpg

I’m delighted to introduce Tri Padukan Purba or Dukan, the latest member of the GeoTraceability Team.  Dukan is based in Jakarta, Indonesia and will be working mainly on Palm Oil Projects.  His particular areas of specialism are Sustainable Palm Oil Production, Best Management Practices and Smallholder Engagement.

Before working at GeoT, Dukan worked for a large oil palm company as Oil Palm Agronomist.  He also has experience working for an international NGO in Indonesia as a Program Coordinator for Better Management Practices for Oil Palm.  Dukan holds a bachelor degree in Forestry from Bogor Agricultural University and a master degree in Wood Science & Technology from University Putra Malaysia.

The number of our customers is increasing rapidly in Indonesia mainly in the palm oil sector.  To provide fast and quality services to our customers, Dukan's primary responsibility is to build a local technical support team.

If you are interested in how Dukan, or any of the GeoT team, could support your work, drop us an email at info@geotraceability.com

A Certification Management System for Cocoa Cooperatives

We are currently partnering with Root Capital to provide cocoa cooperatives and farmer organisations in Cote d’Ivoire access to a digital data collection tool (the Certification Management System).  This allows them to collect data on their farmers and manage the data requirements for certification labels.  This is a new development, and one we think will have a significant impact on the cooperatives and their members.  We hope to see similar systems rolled out in other countries and commodities.  In this interview Hannah asks Mian (GeoT’s country leader in Cote d’Ivoire) about the project and why he thinks it will support cooperatives and farmers.

Hannah: Before discussing the project, can you tell us a bit about yourself and the work you have done in cocoa?

Mian: I am Mian AMOAKON. I am specialist in agricultural value chain crosscutting issues with particular focus on Farmer Organizations strengthening activities to make them more professional and sustainable.  I have over 15 years’ experience in program management mainly in cocoa sector.  I have been GeoTraceability’s Country Manager in Cote d’Ivoire since 2014 and I’m based in Abidjan.

Hannah: What does the Certification Management System let cooperatives do?

Mian: the Certification Management System lets cooperatives:

  • Collect data using a mobile app
  • Meet various certification schemes requirements simultaneously without complications
  • Have digitized data on their members that is accurate, reliable and updated
  • Know key aspects of their producers’ farms, including the area, farm characteristics, farming practices, and the history of production and deliveries

Hannah: Why is this important?

Mian: this is important because it facilitates cooperatives’ work and allow them to:

  • Better track their members, for example assess loyalty level of members by identifying farmers underselling or overselling
  • Better design member support programs
  • Save time and reduce data collection costs
  • Monitor loans and cash advances made to members against deliveries
  • Better data archiving and real-time monitoring
  • Increase their credibility towards their commercial and financial partners

Hannah: How much does it cost cooperatives?

Mian: it cost 12,000$ for the setup fees (upfront charge on Services Agreement signature) and 4,000$ for the ongoing fees (annual charge on the anniversary date of the Services Agreement).  For this project, Root Capital is funding the set-up fee and the cooperatives pay the ongoing fees.  In return, cooperatives give access aggregated farmers data to Root Capital.

Hannah: What is the best thing about the System in terms of how it can help cooperatives and farmers?

Mian: cooperatives spend too much time, energy and money on the data collection process with many risk (for instance loosing filled out paper forms or gathering unreliable data) and most certification agencies are pushing them to adopt digital data collection tools without giving them any support.  One cooperative said that they invest up to 5 million CFA (about 9,000$) a year for data collection.  GeoT’s System gives more credibility and efficiency at the lowest cost to cooperatives.

Hannah: How the Certification Management System helps cooperatives and farmers to access better markets?

Mian: In many instances, farmers and their organisations are not the certificate holders which means that they have to sell their cocoa to international traders and local buyers who hold the certificate and sell certified beans to off takers.  Cooperatives are dependant on aggregators to access certified markets and the premiums paid.

The GeoT Certification Management System allows the cooperatives to access certified markets directly and negotiate their own business terms with off takers.  It is a great way to empower them.

 

 

Profiling Producers to better support them

If your supply base encompasses thousands of smallholder producers, or your development project reaches similar numbers of beneficiaries, you’ll certainly have groups of producers behaving the same way or facing the same issues.  For example, producers whose yields are under the average, producers who never use fertilisers, producers who always deliver top quality, those who receive training but keep their old habits, and the ones who have dependents under the age of 6.

                Profiling them based on set criteria could be an efficient way to better support them and monitor the impacts of your interventions on these groups.  Good databases and systems include query functions allowing you to isolate producers using filters and set criteria.  But in most cases, you’ll need to repeat the same iteration to obtain the same result.  For example, female farmers having field of less than 1 hectare, having 4 children under 16 and a yield under the average if you want to monitor this specific group.

                Our web platform has a powerful feature called the User Story.  With this feature, users can create groups of producers and save their stories by giving it a name: Female with less 1ha, with 4 and up children under 16 and yield under average.  This means you can access this search repeatedly without having to redefine your criteria.

                Suppose at the start of your program you have 46 women meeting the criteria mentioned above.  Your objective should be to decrease this number overtime and support these women to improve their yield, despite the small size of their farm and their obligation toward young dépendants.

Screen shot from the web platform showing 46 female famers who meet the criteria selected

Screen shot from the web platform showing 46 female famers who meet the criteria selected

In addition to being able to save set criteria, the System is dynamic and updates the results as data is added.  This means you can set the criteria at the start of the project and then assess how the results change over time.  So, you could build a complex M&E framework with various milestones to reach overtime.

Screen shot showing a pre-defined list of searches used for monitoring and evaluation

Screen shot showing a pre-defined list of searches used for monitoring and evaluation

The User Story also has the ability to show you when certain criteria are not met.  For example, you can create a story for the producers who only deliver C quality, the lowest.  But you can reverse the result and obtain the producers never delivering the C quality.  This is very useful to instantly create control groups.

Screen shot showing the ability to invert search criteria

Screen shot showing the ability to invert search criteria

The System lets you modify your existing stories by adding or removing criteria.  This way, you can follow your groups as they evolve and bring them to a next level.

You can learn more on the User Story by getting in touch with us (https://geotraceability.com/contact-us/).

Traceability: implementing tracks for transparency

Hannah Hobden’s speech at the Partnership meeting of the World Cocoa Foundation on October 24, 2017, Washington DC

Hello – my name is Hannah Hobden. I work for GeoTraceability and I’m here to challenge you to turn full traceability – from bean to bar - from an aspiration into a reality for the cocoa sector.

Traceability systems are the operational infrastructure on which you hang data to create transparency. An effective system requires full traceability from bean to bar and the ability to capture data as the product moves through the supply chain. Technologically this is possible, as I will show later. The challenge is how to implement a system in cocoa. To do so will require collaboration and, ultimately, a willingness to move away from a mass balance system – because mass balance effectively creates a wall against transparency and traceability.

But before we go any further, what do mean I mean when I say that a full traceability system provides the operational infrastructure to create transparency? Well I like to think about it in terms of a train track. A tracing system is like the railway tracks that link different components of the supply chain – for example farmers, warehouses, ports, factories …. Once the tracks are in place different information can move along them between the supply chain stakeholders. In the case of cocoa this could be information on the producers, such as data relevant for monitoring gender equality, living income, deforestation, use of child labour. Information can be collected on the price and bonuses farmers receive for their cocoa and this can be compared with the amount of money received by the cooperative. In the past we have created risk assessments for child labour at a farm level and we are currently in discussions about doing this at a community level. Having this risk assessment data as part of a traceability system would mean a final batch of cocoa having a child labour risk level associated with it. Data can be collected on the cooperative, warehouses, ports, factories. The quality of the cocoa can be tested and recorded at different points along the supply chain. What I am trying to demonstrate is that once the tracks of traceability are in place, multiple levels of data can be added. But, to be most effective, tracing data needs to start with the farmer and a bag of cocoa and go all the way along the supply chain. Mass balance interferes with this because it creates a barrier against the movement of data and information and so cuts the tracks off between farmers and final customers.

So, you might now be thinking, that’s all very well Hannah but it’s not realistic to achieve. But I’d like to challenge you and say that with collaboration and investment into existing operational frameworks it is possible. I think the most inspirational story to show what can be done is from the palm oil sector. As I’m sure you are all aware, there are significant challenges in palm oil around deforestation. Many of the consumer brands have made promises to have supply chains free from deforestation and have decided to use traceability as one tool in achieving this. However, making the link between mills and farmers was a significant challenge.  As in cocoa, there is a complex web of smallholder farmers, cooperatives, and middle men. For a while it seemed hopeless. But two years ago, we started a project which was a collaboration between IDH, Wilmar and ourselves to pilot a tracing system linking farmers to fresh fruit bunches, fresh fruit bunches to middlemen, and middlemen to mills. The system was simple and effective and demonstrated the possibility of laying the tracks of traceability between the farmers and the mills. This initial pilot allowed us to develop a commercial model, which we are now able to roll out to other mills, this time without the need for donor funding. And now the basic tracing system is in place, we are able to increase transparency though data collection. So, we are collecting data on the farmers’ production methods, which allows us to create business plans for each farm for productivity improvements. We know the exact size and location of each field and so can monitor over time whether these fields encroach into forest. We can record what training each farmer has received and any follow-up visits they’ve had. We have delivery records of the amount of fruit a farmer sold, on which date and for what price. We can record all this information again when the middleman sells the fruit to the mill. A key factor in palm oil is that the fresh fruit needs to be processed within 42 hours of harvesting. So, we have started implementing an alert system which notifies the mill when fresh fruit bunches have been collected from the farmers but not delivered to the mills for processing – this means the mill can take actions to retrieve the fruit before it goes off. The technology is also available to send text messages to the farmers informing them of when trucks will be sent to collect their fruit, or when training will be happening on a topic. This simple tracing system from farmer to mill can then be linked with the tracing systems already being implemented at mill level and further along the supply chain and relevant data passed along.

This has all been achieved as a culmination of:

  • political pressure for transparency around deforestation,

  • commitment by organisations to traceability,

  • collaboration between different stakeholders both in terms of funding and operationally, and

  • pure determination.

I am not saying the issue of deforestation is solved in palm oil by any means, but what I am saying is that something which seemed impossible three years ago – having full traceability along the supply chain – is now possible.

So, what needs to be done in cocoa to make traceability a reality here too? Others in this session are discussing transparency at a policy level so what I want to focus on are some operational solutions. Firstly, from a technology perspective there are plenty of solutions out there. The key is that technology should be collaborative, in the same way that organisations must be. Therefore, when investing in supply chain data and traceability systems it is essential that they are interoperable – this means regardless of who is providing the technology, it will be able to link to other systems. So, overtime you can link tracing data with mobile payments, cooperative sales records, soil testing, financial support, farmer loyalty schemes etc. Secondly, we need to start implementing traceability from farmer level. At GeoT we have worked with the traders and exporters to implement tracing systems. But the issue here is that these organisations do not usually use the systems that are implemented – they pass the data onto their clients, who get frustrated with the fact that slightly different data is being provided to them in multiple formats by different organisations, but who usually do not have the power to demand specific data from their supply chain.  So, my suggestion is to copy the palm oil model and develop a tracing system that can be implemented initially by cooperatives and build up from there. This is particularly important to do because it is at this level that we need to tackle the significant challenges of living income, deforestation, child labour, modern day slavery, and climate smart agriculture. Commercial models need to be developed for systems that allow cooperatives to take charge of their own data collection and provide traceability data to the people they sell to. We have already started working with Root Capital in Cote d’Ivoire to provide a basic data collection system to cooperatives but more needs to be done to enhance this and ensure relevant data is captured and effectively passed along the supply chain.

I expect momentum will develop around traceability in cocoa as we see continued political pressure for it by national governments and internationally; organisations needing to meet their own traceability commitments and so having to start tackling the traceability problem caused my mass balance and not knowing who their farmers are; and collaboration between organisations to develop a commercially viable system that works for the private sector.

So, I hope I have inspired you today with the possibilities for transparency and communication along the supply chain which are possible when full traceability is in place. I’ve challenged you for the need of greater collaboration to make traceability a reality for cocoa and have suggested a simple place to start is with farmer organisations and cooperatives.

Providing tools to make your data talk

                Problems occur for organisations when they start collecting data and then, after the data has been collected, ask themselves what they can do with it.  Often, they realise that they have not collected a key piece of data, or that they have collected too much, and so have paid for data they do not need.  So, our advice to clients is to be 100% clear on how you will use the data you collect BEFORE you collect it.  This can be a frustrating task at the start of a project when everyone is excited about what the data will show and just want to get going with the data collection, but it’s like building the foundations for a house – you spend a lot of time digging down with little to show for your efforts, but without this investment, the building will fall.  A clear data framework is the foundation for any project involving data collection.

                Once the data has been collected, you need to make the most of your investment.  Using the right tools to analyse the data helps increase the value of the project.  Sometimes we see investment wasted because the data that has been collected is not analysed effectively.  This is something we want to help clients avoid and so have developed tools on our web platform to help with data analysis.

                In a GeoTraceability System, all the data gathered on each smallholder (for example production, household, training, credit, payments, inputs provided) is recorded in a ‘supplier profile’ (see diagram 1).  It is also possible for the system to make automatic calculations using the data gathered – for example if you know the size of a farm and the annual yield, the system can automatically calculate yield per hectare.  If delivery data has also been collected, you can estimate the amount of side selling occurring.

Diagram 1: Supplier Profile

Diagram 1: Supplier Profile

In addition to viewing the data on each individual farmer, the results for all the farmers are aggregated.  The results can be viewed in a number of different formats: bar graph, pie chart, table, and thematic map.  At any point, you can capture the result, a graph for example, by saving it on a pin board (see diagram 2).  The pin board lets you group results under different categories, which you can manage.  The results can then be integrated into a PowerPoint or Word document at a later date.

Diagram 2: Pin board

Diagram 2: Pin board

                You can also combine different indicators and do a multi-criteria analysis.  For example, the producers who delivered in February, have over 40 years old and apply over $500 value of fertiliser.  This iteration creates a ‘story’ that you can save and re use after (see diagram 3). It can also be used to monitor project indicators, such as the number of women who have been trained on how to prune.

Diagram 3: User Story

Diagram 3: User Story

If the above functions don’t give you the insight you’re looking for, you can also us the Pivot Table on the web platform (see diagram 4).  Here different pieces of data can be seen in relation to each other as you make a simple matrix, for example, the distribution of age per gender.  But you can also add a third dimension, like production, to see if the gender and the age impact production.  You can express the result as the average production for female farmer in the range 21 to 30 years or the tonnage produce by this group.  You can also add a forth or a fifth dimension and so on to see if other factors impact production, like the household revenue or the average distance to the nearest clinic.

Diagram 4: Pivot Table

Diagram 4: Pivot Table

Once you’re happy with your analysis, you can save it on Excel on a click of a button (see diagram 5).

Diagram 5: Pivot table results in Excel

Diagram 5: Pivot table results in Excel

With the GeoT tools you can analyse your data from any angle.  For example, show me first the producers who grew peanuts on their farms, and then, looking at only this sub-section of producers, which containers shipped to my clients contain their cocoa beans.  Or the other way around: one client says they found peanut residue in a batch of cocoa butter they processed with the beans you supplied, so they want to know if some producers who have contributed to this batch grow peanuts.  This shows how you can easily understand the power of the System to prevent contamination or to manage product recalls, as an example.

You can learn more on data analysis by getting in touch with us (https://geotraceability.com/contact-us/).