Addressing the challenges of smallholder forestry in Kenya
Every once in a while, we at Simosol receive a client who’s project faces challenges which need to be addressed from a fully integrated approach. This is the case of Komaza, a forestry company based in Kenya.
The operations of Komaza are dispersed between two coastal counties where eucalyptus and melia plantations coexist with crops and other land uses. Komaza operates in a “micro-forestry” model, supporting the establishment of thousands of woodlots, conducting harvesting operations, processing wood and selling finished products. This business model strengthens the local economy by providing thousands of farmers with an income stream which complements their short-term crops. However, this business model presents various challenges.
First, as Komaza is managing forestry data from thousands of woodlots, information management can become problematic. Foresters know the problems in using worksheets when managing plantation data - they become heavy, risky, and inefficient. Second, the silvicultural activities performed on the woodlots are not under the responsibility of Komaza. As a result, the tree farms are highly heterogeneous, and therefore their growth and yield are considerably complex to model. Most forestry modelling tools out there are not flexible enough, basing their estimations on predefined parameters for a species and region - none of them offering predefined models for eucalyptus in Kenya.
Third, for wood processing and sales operations, the company needs to accurately predict the future wood flows and optimize their procurement from the multitude of woodlots. Therefore, this presents challenges in simulation, optimization, and scenario comparison: “if we need to continuously satisfy the capacity of our plant; when, where, and how much should we harvest?”
Fourth, Komaza, like most forestry companies, needs to continuously consider different processing options for their harvested wood in order to stretch their product portfolio towards sectors where they can successfully compete. Each scenario needs careful considerations, notwithstanding dealing with the aforementioned challenges.
Fifth, once a company has grown, needs for valuation of the project become a priority, for which the data needs to be trustworthy, the models need to be accurate, and the projections need to consider all the operational and financial restrictions specific to each company. Sixth, once you know the value and state of your assets, the monitoring of their development is also of prime importance.
These challenges need to be overcome in an integrated manner. Why? Because you need to trust your data to make good models. You need to trust your models to make good projections. You need to trust your projections to make a good scenario comparisons and asset valuations. And you need to periodically monitor of all these aspects in order to have a solid base for producing high quality strategic information for future decisions.
Simosol is currently providing Komaza with solutions for these challenges, including modelling services and training for generating accurate and customized growth models based on their data, software for managing the data and modelling and comparing different planning scenarios, and valuation services for appraising forest assets. As part of these services, we are identifying needs for operational improvements and studying the possibilities of remote sensing in mapping and monitoring of the tree farms.
It is truly exciting to be part of the unique smallholder forestry business model development in Kenya!
The article was originally published on LinkedIn.