Value chain development nurtures changes in attitudes of market actors and relationships between each other. Through this new patterns and routines of behaviour are incubated and when successful these deliver transformations in the competitiveness, inclusiveness and equitability of market systems. While competitive upgrading of a value chain or shifts in the distribution of value across market actors are objectively observable, the more intangible emerging properties of the system – such as changing attitudes, relationships and routines of behaviour which result - are more difficult to measure. It is essential to track these however since these are foundational leading outcomes for transformations of the market system that are sustainable and for the development of the adaptive capacity of the system in the future.

1. Know What You Know: Harnessing Tacit Knowledge in
Value Chain Monitoring
The Groove Learning Network M&E 4 VC Series
Prepared by Alexis Morcrette (Practical Action) with Christian Pennotti (CARE)
The GROOVE Network forms part of the USAID-funded New Partners for Value Chain
Development Learning project
Draft 1.2 - October 2011

2. Attitudes, relationships and routines of behaviour
Value chain development nurtures changes in attitudes of market actors and relationships
between each other. Through this new patterns and routines of behaviour are incubated
and when successful these deliver transformations in the competitiveness, inclusiveness
and equitability of market systems. While competitive upgrading of a value chain or shifts
in the distribution of value across market actors are objectively observable, the more
intangible emerging properties of the system – such as changing attitudes, relationships
and routines of behaviour which result - are more difficult to measure. It is essential to
track these however since these are foundational leading outcomes for transformations of
the market system that are sustainable and for the development of the adaptive capacity
of the system in the future.
Good management in complex systems: responsiveness and adaptive capacity
Understanding how attitudes, relationships and routines of behaviour amongst market
actors are changing is not something that programs can afford only to measure at the end
of an intervention. Market systems are highly complex, made up of intricately
interconnected and interdependent parts, and are ever-changing and adapting. This means
that even careful design and planning will only prepare a program partially – there will
always be surprises in implementation. Market systems are also highly context specific, so
there are no reliable recipes for success (add two teaspoons of sugar), only guiding
principles (use a spoon not a knife to add sugar).
Difficulties and even failures are to be expected, at least at first. What is important is to
be able to learn from and react to difficulties and failure. To do this, program teams need
to be responsive and adaptive:
- Responsive to the information feeding back from the market system about the
effectiveness of their actions;
- Adaptive based on continually changing understanding of the context.
For example, in a rice value chain program in Ghana, Engineers Without Borders (EWB)
worked with input dealers, trying to facilitate them to expand their businesses and
provide better information to farmers on chemical and fertilizer use. On paper there was a
promising opportunity to facilitate a change in business behaviour which could lead to win-
win outcomes: an expansion of business for the input dealers through customer loyalty,

3. and improved access to quality products and information for farmers, contributing in turn
to better practices and an increase in yield.
In practice though, none of the input dealers were interested. The reality was that each
input dealer was selling to their network of family and friends. This was well understood
and informally accepted by all. Beyond a little give and take, everyone had their own
store of inputs. When the situation of arose that a customer asked for an input of which
the dealers had no stock, they would recommend another store nearby instead of
considering procuring it themselves for the customer. Trying to facilitate change here was
like squeezing water from a stone: the field coordinators were trying to increase
competitiveness in an environment that wanted to maintain a status quo of networks of
family and friends, with a low risk, low input, low output equilibrium.
Realistically EWB could not have known about the resilience of this low equilibrium
situation in advance, and ex ante it made sense to try to change it. Only in retrospect did
the difficulties become clear.
Good management in complex situations is not about trying to avoid these ‘failures’ but to
learn from them, and improve in the next iteration of the program intervention. EWB’s
effectiveness should be judged not on this stumble, but on how they responded to
information about these difficulties and their ability to adapt to their continually changing
intelligence about the system.
Does a traditional monitoring system serve responsive and adaptive programs?
Typical monitoring systems and the indicators they track don’t create the kind of
knowledge that is very good at supporting responsive and adaptive decision-making. This
example, loosely based on some of Practical Action’s experiences facilitating the dairy
market system in western Nepal, illustrates this:
In hill districts of Nepal Practical Action’s dairy program is facing the challenge of
strengthening the ability of smallholder dairy farmers to connect with district
storage facilities more efficiently and reduce milk wastage. A series of market
analyses told the team that dairy cooperatives could become strategic actors to
overcome the challenge. The team worked to strengthen the cooperatives and
their leaders.

4. On paper, this plan looked robust but in reality the process proved difficult. The
program’s monitoring system tracked outcomes around quality and volume of milk
going through the cooperative and membership rates of poor farmers in
cooperatives. In some cases it told program management firstly that milk that
cooperatives were collecting wasn’t improving in quality. Secondly despite
producing increased volumes and quality of milk and having newly connected
access to cooperatives many poor producers were not selling to them. What the
management also needed to know was why that might be.
Field facilitators were in a position to see what was going on. Why wasn’t the
quality of milk improving? The cooperative leaders had a strong interest to sell
their own milk to the cooperatives, regardless of its quality. They also wanted to
maintain their community relationships with farmers contributing poor-quality
milk. The district storage centres had weaker demands on milk quality than
expected.
And why were many poor farmers not selling to the cooperatives? Rather than
welcoming new smallholder farmers to join the local cooperatives, existing
members preferred to protect their capture of cooperative profits by keeping the
membership to the cooperative small. Non-member farmers are allowed to sell
their milk to the cooperatives, but could not access the benefits that members
enjoy. Reacting to this attitude, some farmers preferred not to sell to the
cooperatives.
This example highlights how the formal and traditional monitoring system of this
intervention was able to pick up that something was not going to plan, but could not
explain why. In contrast the field facilitators, who frequently visited the cooperatives to
supervise activities and provide business coaching where required, naturally picked up on
the community power dynamics at play and could understand what was going on.
What information, when and for whom
Practically speaking then, what should a program do to be as responsive and adaptive as
possible?
First of all, a program must know what it needs to know: A program must keep track of
the intangible properties of market actors and their interactions with each other on which
sustainable, tangible market transformations are founded. These properties include:

5. - Market actors’ attitudes towards themselves: levels of confidence and motivation;
- Market actors’ relationships with each other: their prejudices, respect and trust;
- Market actors’ interests or incentives that drive their business behaviour;
- The patterns of behaviour and routines of practices themselves.
Furthermore, a program must know what to look out for: It must also track how its
interventions are affecting these properties, and be open enough to gather information
not just about expected consequences, but also the unexpected feedbacks that are
characteristic of a complex system.
Thirdly, a program must know when to know: What is important is not just what kind of
information needs to be collected, but also how it must be packaged for use. Since the
objective is for the program to be responsive and adaptive, the critical factor here is
timing. Information must be collected, collated, analysed and presented in a state to
inform decision-making quickly, ideally as close to real-time as possible.
Finally, a program must know who knows and who needs to know: Given the content of
the knowledge that is desired, it is primarily the field staff who have access to it. The
field coordinators and facilitators are the ones who frequently interact with market actors
and are able to get a sense of their attitudes and interests and directly observe their
behaviours. It is also the field coordinators and facilitators who are the ones who can
gauge immediate effectiveness of intervention activities against desired outputs and
leading outcomes.
Those who need to know this information are the program decision-makers. Top level
program managers are obviously very important decision-makers, but in value
development program decision-makers are typically found all the way along the staff
structure. Some examples: field coordinators tend to have decision-making control over
what specific strategies to take in facilitating activities; cluster or area managers can
make choices about the sequencing of some activities, and allocation of in kind resources,
even if they don’t have control over budget allocation and the program of activities.
In summary, a responsive program relies on knowledge:
- About intangible properties of the system and the early and lagging effects of
program interventions on these properties;
- That is quickly turned over;
- That is mostly learnt by field staff and useable by decision-makers.

6. Know what you know
The good news is that the kind of knowledge that satisfies these characteristics is
knowledge that can be created by any program with often limited additional resources.
The bad news is that harnessing it requires an approach – system and process – quite
different to traditional monitoring systems.
This example describes the experience of a field coordinator in CARE’s ADAPT project in
Zamiba:
A field coordinator is walking to her truck after just wrapping up the second of ten
planned rural seed fairs she has organized that month. This is the first time she is
leading these events on a new project intended to improve smallholder access to and
use of improved inputs. Historically, these have seemed expensive, difficult to access
and unreliable, often not performing as advertised. The fairs are also intended to
increase private sector interest in pursuing the smallholder market, which from their
hubs in Lusaka still seems fragmented and not terribly worth investing in.
As she walks away, the field coordinator notices that a number of producers are
crowded around, talking with two reps from a new seed supplier. She passes a second
group and can overhears them talking about the skit on good agricultural practices. It
was pretty funny and they learnt a lot they say. The field coordinator is happy that
the ministry of agricultural extension agents finally committed to doing it. There
were some empty booths, of course, because two suppliers hadn’t showed up but
she’s just received a text from one that attended praising the event and asking about
the upcoming ones.
ADAPT is tasked with developing a sustainable network of over 600 agro-dealers, and seed
fairs played a key role in building demand and interest across all actors including input
suppliers, agro-dealers, entrepreneurs, producers. Ultimately ADAPT has been quite
successful with over USD 35 million worth of inputs have been sold through the network
over the past three years. This was not always the case however and the seed fairs
themselves evolved over time as staff learned how best to get people to attend and how
to make the most effective use of the time at the fairs.
This example highlights some of the myriad of things that field staff observe as they
facilitate intervention activities. These informal observations provide a basis on which
field staff can make a judgement about how well the activities go. Their opinions of how
well the activities have gone are more than just gut feelings. They are informed by

7. conscious and semi-conscious observation and experiences that together build up a body of
evidence to support the judgement. A field staff may not be able to pin down this body of
evidence, but their judgement may nevertheless be very informative.
This kind of knowledge of field staff is tacit knowledge: understanding developed through
experience, difficult to transfer because its foundations are built implicitly. Importantly,
the headline impression or judgement of tacit knowledge is can easy to communicate with
others. What is difficult is to justify this impression. In the example from ADAPT when the
field coordinator picks up her phone to tell her manager about the fair, she will probably
be able to say that it went well and that momentum amongst market actors for change is
building well. She might not be able to explain why she thinks that (she might not have
been conscious of the effect on her impressions of seeing the producers crowd around the
input supplier reps).
When tacit knowledge of field staff is properly harnessed, it can serve precisely the needs
of responsive and adaptive program decision-making:
- Intangible properties of the system and the early and lagging effects of program
interventions on these properties – Field staff may (often do) need guidance to
condition their conscious and sub-conscious to look for the right signals about
markets’ attitudes, relationships, behaviours and practices before and after
intervention activities. This will enable their tacit judgements to be well-informed.
However, their views ‘from the field’ are precisely the perspective from which
information about intangible properties of the system and effects of program
interventions can be seen.
- Quick turnover – The process of internalising information, building evidence and
making judgements is all semi-conscious in the case of tacit knowledge and
happens quickly over just a few days (at most) after the activity. This means that
field staff can begin to share their impressions and the signals they observed (if
they have received some guidance on what to look out for) with other project staff
within days of the activities.
- Learnt by field staff and useable by decision-makers – Clearly field staff tacit
knowledge comes from the field, and if the right space is created for them to share
their impressions openly and honestly, it can be made explicit and transferred to
other decision-makers (remember the field staff may themselves be decision-
makers).

8. Harnessing tacit knowledge – Key principles
No one knows exactly what the right approach to harnessing tacit knowledge looks like.
That’s because it is context specific and therefore looks different in different programs.
Just like market systems, knowledge systems are complex and so the analogy with the
spoon applies here too.
The e-consultation confirmed however that there is a broad agreement about what some
of the characteristics of an effective system comprise of and there is also considerable
consensus on what a good process to get there involves. We are all aware of what the
challenges are too.
- Ensure a common understanding of the entire program logic across all staff:
Program staff should never only focus on their immediate responsibilities and
activities. They should also keep in mind how these contribute to the logic through
which the program hopes to achieve its objectives. Only by continually placing
individuals’ responsibilities and activities within this wider understanding will it be
possible for staff to keep an eye out for information that may be useful for
decision-making. It is particularly important to emphasise how leading outcomes
around attitudes, relationships and routines of behaviour are critical to achieving
lasting impacts in value chain competitiveness, inclusion and equitability. This will
enable the field staff to recognise how their activities on the ground contribute to
the program’s objectives, not simply through the delivery of activities, but only if
the activities result in these leading outcomes.
Participatory results chain (a.k.a. causal model) mapping, where staff from across
the program work together to develop the logic of the program, is a test tool that
can enable this common understanding.
- Orientate field staff towards ‘killer’ assumptions: There is always a huge amount
of things that field staff can look out for, so it is always useful to spend some time
prioritising some areas of focus. Areas of focus can be defined against ‘killer’
assumptions in the program’s logic at the end of the participatory results chain
mapping process. A killer assumption refers to a critical assumption underpinning
the logic of a program, an assumption which if it does not hold will make it
impossible for the program or a major component of the program to achieve its

9. objectives. Further orientation can take place at the field level, the day before an
activity, or even in the vehicle on the way to an activity.
- Create a culture of sharing and learning: There needs to be frequent and regular
spaces created for field staff to discuss with decision-makers their observations.
These spaces, and the wider culture of the program, must emphasise critical
reflection, honest sharing and continual learning if they are to be successful at
communicating tacit knowledge across the program.
- Document the discussions: All program decisions must be transparent. If tacit
knowledge staff is to be used to help decision-makers, it is imperative that
discussions between field staff and decision-makers is documented so that the
rationale for any decision has a paper trail. Documenting discussions involving tacit
knowledge also has other benefits. Firstly, each observation of a field staff is only
a snapshot. Only by bringing together a number of similar observations over time or
across several field staff can a broad picture be built. Documenting discussions
enables decision-makers to consult earlier comments made by field staff to help
them build up this picture. Secondly, tacit knowledge can be useful for evaluators
and researchers looking at the program. Their activities are retrospective and
therefore documentation of discussions will allow them to make use of tacit
knowledge. Remember, documentation need not be written. It can be recorded or
video-taped material.
- Align the incentives of program staff: Unless the incentives are aligned to harness
tacit knowledge, no system or set of process will make up for this. Field staff must
see critical reflection and honest sharing as necessary for their own professional
performance. Similarly, decision-makers must see feel that listening and making
use of this information passed onto them by field staff will genuinely contribute to
better decision-making, otherwise they will not invest the in kind resources
necessary to make the system effective.
- Regularly revisit the logic and of the program and the prioritisation of areas of
focus: Since the context (market system) is prone to change, and the program may
adjust its approach during implementation, the program’s logic may also change. It
is therefore important to bring the program staff together to discuss this logic not
only at the beginning of the program, but at regular occasions throughout the
project. Changes in the logic will also imply changes to what signals are most

10. important for field staff to look out for. The prioritisation of signals should
therefore also be revisited regularly.