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Trying Hard Is Not Good Enough
Results Accountability 101 DVD
Postings on Various Topics
by Mark Friedman
(Replaces the RBAOBA Google blog site)
(most recent first)
10. Questions and answers from Wales Master Class
9. Organic vs. architectural change
8. The performance of teachers.
7. How to organize the work of "turn the curve" tables.
6. The population role of education.
5. Shortcut method for choosing
Measures categorized on the basis of what question they answer.
3. Creating results culture
the success of population level strategies.
1. Next Generation Contracting - Key Provisions.
This space is devoted to the presentation of
insights, advice, and general rambling on
topics related to RBA/OBA. This replaces the Google blog site which never
really worked very well. If you have questions about RBA/OBA that you would like
to see addressed here, please send an email to. firstname.lastname@example.org.
January 22, 2010
& Answers from Wales Master Class: April, 2010
Posting #10 October 2, 2010
understanding [RBA principles] more important than rigid fidelity to the RBA
sub-populations okay? How many layers can you have between services at the
bottom and high level? Does it matter?
we have a hierarchy of outcomes? [e.g. by sub-population]
MF do a critique of Welsh Performance Management Framework as he did for
similarities and differences are there between performance frameworks
(generally) and RBA accountability?
credible is use of self-reporting tools on soft outcomes against more
do you turn the curve when there is a lack of available data, or data takes
time to come through? What do you do in the meantime?
Posting #9 April 14, 2010
believe the case can be made that much if not most, philanthropy in this country
and around the world is highly inefficient at creating the change we want. This
inefficiency derives in part from the difference between “architectural
change” and “organic change” processes. Architectural change is the
“design and implement” model at the heart of most government programs and
most grantmaking initiatives. Organic change is the “plant and grow” model
we see in grassroots movements and self organizing systems. Architectural change
is less efficient because it requires a constant infusion of new energy (money)
to keep it going.
Organic change is often self-generating and self-renewing.
have plenty of examples of organic change processes, incentives perhaps being
the most obvious. Incentivize certain behaviors (with money, recognition, etc.)
and people naturally respond with the desired changed behavior. RBA is, at its
heart, an organic process. Show people an indicator or performance measurement
curve that’s not OK and watch them organize the partners and resources to turn
the curve. Embedded in any good RBA practice is the idea of what works or theory
of change. And embedded within theory of change is the idea of “theory of
grantmaking,” that part of the theory of change discussion unique to those who
have money to give away.
I was at CSSP, I proposed some grantmaking ideas under the rubric of “Most
Results for the Least Money.” These were inexpensive organic change ideas
you can link to here, as examples of the type of thing I am talking
about. Foundations, United Ways and other funders should consider convening a
Theory of Grantmaking advisory group to look at how you can get the most change
(or best results) from the investment of funding and other resources. Such a
group could examine the wide range of organic and other grantmaking strategies,
examine the evidence for these approaches, and make recommendations on how to
balance the grantmaking agenda to greatest effect.
performance of teachers
Posting #8 April 14, 2010
Pretend, for a moment, that I can split you into two
people and give you two separate teaching assignments for one year. You, Version
A, are given a 3rd grade class in an upper middle class neighborhood.
You, Version B, are given a 3rd grade class in a poor urban
neighborhood. In both cases, your job is to teach the children in your class to
read. At the end of the year, you will be evaluated on the basis of the average
reading scores in your classrooms. The one with the higher score will be
retained. The one with the lower score will be fired. Which of you will be fired
The answer is obvious. The children in the poorer
classroom started out with lower scores and finished with lower scores. You did
a lousy job teaching this class. You are a bad teacher and deserve to be fired.
OK. That’s unfair. Let’s change the rules. Let’s
look at the amount of improvement in reading from the beginning of the year to
the end of the year. Well the one of you who taught in the poor school still
gets fired because the children not only started off behind, but more of them
have learning difficulties, live in homes where there are no books and have
parents who can’t read.
OK. That’s not fair either. You can’t compare
classes in two different schools like that. Let’s back up and give you two
different classes in the same school. But you will quickly see that the same
things will also happen between any two classes in the same school. Some
students will do better or worse for reasons that have nothing to do with who
you are or how good a teacher you are.
Fast forward to the 2012 Olympic Diving Competitions.
Diver A does a triple back flip off the high dive but misses the water entry.
Diver B does a swan dive off the low dive but nails the entry. How can we
compare Diver A and Diver B. The Olympic Committee has an answer: “degree of
difficulty.” One dive is harder than the other and is judged differently.
The same principle could be applied to teaching, but
imagine how much harder it would be to assign a “degree of difficulty” to a
child. Now try creating a degree of difficulty for a whole classroom. Now think
about how to adjust that degree of difficulty over the year as the class changes
when children move from one school to another.
There is a lot of discussion today about getting rid of
“bad teachers.” You would think from hearing this that the problems in our
education system are caused principally by a large number of bad teachers that
the system refuses to fire. One could, of course, make a similar case that the
problem with our legal system is a large number of bad lawyers that the system
refuses to debar. The problem with the medical system is a large number of bad
doctors that the system refuses to decertify. The point is that there is no
simple way to use achievement test data to evaluate teachers, any more than there are simple ways
to use patient data to evaluate doctors or law suit data to evaluate lawyers.
Anyone who believes otherwise doesn’t know very much about teaching (medicine
This does not mean that we can not use data to improve our education system.
Using data to drive school improvement is different than using data to fire
teachers. When schools make use of data to drive improvement it is usually site based
(or school level) data, not individual teacher data, (e.g. total school 3rd
grade reading scores). Schools have a place where trend data on achievement test
scores, attendance rates, graduation rates and rates of teacher retention are
prominently displayed. There is an inclusive process for interpreting this data
and taking action that involves a wide range of partners, including teachers,
principals, superintendents, parents, business leaders, the faith community,
elected officials, the media and the students themselves.
When school improvement is managed this way it has a
much greater chance for success and is far more constructive than blaming
teachers or anyone else. The vast majority of teachers are dedicated
hard-working professionals who often work under extremely difficult conditions.
People who suggest that fixing schools equates with firing teachers do so
because it is easier to name scapegoats than do the hard work of making our
schools better. We will never get anywhere if we misconstrue the very nature of
the problems we seek to solve.
Note: I am aware that I have touched only lightly
on school improvement planning. Education is addressed in many places in
"Trying Hard Is Not Good Enough," but see in particular the section
"Unified Planning for Education" on pages 118-119. I have also not
endorsed any particular method for teacher evaluation (e.g. peer review). I
believe that individual performance evaluation in education or any other service
system is a by-product of good supervision. When I was a first year high school
math teacher I received essentially no supervision or support which is one of
the reasons I only lasted one year. We have generally done a poor job of
training people to be supervisors in the public and non-profit sectors.
Supervision and individual performance evaluation must be addressed together and
are topics for future writing. See pages 81, 84 and 105 for some more thoughts
on these subjects.
How to organize the work of
"turn the curve" tables
Posting #7 February 16, 2010
A "turn the curve table" is a group of people who come
together with the intention of turning one or more population indicator (or
performance measurement) curves. It is a good idea for people working together
in this way to have experience with the "Turn the Curve Exercise" and
some grounding in RBA (either from an RBA 101 workshop, reading the RBA book or
watching the workshop DVD.) Following is some supplementary advice recently
given to support the work of several newly formed state level turn the
curve tables. References that might identify the specific state have been
At the start, it is always important to remind people that
turning any curve is a hard thing to do. Population level indicator curves
require the efforts of many partners, usually take years, not months, and can
not be turned through the single cycle development and implementation of a
static plan. Sustained efforts and living plans are the only way.
In general, the works groups can benefit by following the steps
laid out in the "Turn the Curve" exercise. In fact, this would be a
good way to structure some or even most of the first meeting. The turn the curve
process is designed to be iterative and so subsequent meetings could constitute
successive passes at this process. The best way to think about successive
meetings is to address every step in the process at every meeting. At each of
these passes the work gets better. The use of time limits on each part of the
meeting can help groups develop this discipline.
Following are a few notes on some of these steps that I hope
will be helpful.
1. Forecasting: Most people have little experience
with forecasting. Forecasting is discussed in some detail on pages 56 to 59 of
"Trying Hard Is Not Good Enough." And there is still more guidance on www.raguide.org.
The two most important things to remember about forecasting is that (1) it must
be politically credible, and (2) it must represent our best thinking about where
the line is headed if we don't do something more or different (i.e. not where we
want to go, but where we are going if we don't do something to
change.) This might involve more than one forecast using different assumptions.
However, when multiple forecasts are used, remember that
forecasting quickly loses its utility if there is too wide a variance between
2. The story behind the baseline: The story is the place
where we address causes. There is a natural tendency to give this part of the
process short shrift. But the "story" is the diagnostic step in the
process. Failure to adequately address the story would be like a doctor
prescribing medicine without first diagnosing what is wrong with you. The story
need not be about just what is wrong. It should address both what is working and
what is not working. The story can and should reflect a rich array of
perspectives and there should be an opportunity for a wide range of people to
weigh in. This will almost always create a complex picture with competing
or even conflicting interpretations. But this is OK. The story does not have to
be resolved into a single monolithic consensus before other parts of the process
can continue. A rich picture of causes will lead to a much richer discussion
about choices for action.
3. What works to turn the curve. This is the part I
most wanted to write about, because there is less written guidance on how to
have this discussion than for some other parts of the RBA process. It may be
helpful to segment the "what works" discussion as follows:
3a. In the Turn the Curve exercise we ask people to wear
different hats so that a broader range of partners can be represented. In the
real work, the discussion of existing and potential partners must be deeper
than this. The groups may find it useful to begin to create an inventory of
government and non-governmental partners in (at least) two broad classes:
partners who are now actively engaged; partners who need to be actively
engaged. All good action plans include components to recruit and engage
3b. A well developed partners list allows the discussion of
what works to proceed partner by partner, starting with the various partners
in state government.
3b1. Think of what the state can do that is no-cost
/low-cost and what it should do with it's next dollar to turn the
curve. The "next dollar" idea can help focus the discussion
quickly on the most highly cost effective measures. Note that the next
dollar does not have to be a "new" dollar, but the next available
dollar whether new or reallocated from another use.
3b2. What can other partners do, nc/lc and next $ and how
can you recruit them to be part of the process. This is the same as the
state discussion but for each partner. It's very helpful if these partners
are part of this discussion, since "telling people what they should do
to help" is usually counterproductive. Partners should have the
opportunity to tell what they are already doing and to offer up new
contributions without being pressured to do so. In the end, Everyone should
get a share of the credit for the success of this work.
3b3. Of all these ideas, which ones do we most highly
recommend in the short (this year), medium (next year) and longer term (3 to
5 years)? There are many ways to have this discussion and display these
recommendations. In every case the groups will need to exercise judgments
based on some criteria. One approach to doing this is offered in the book on
pages 43 to 45, but there are certainly other possibilities. Most
importantly, the groups should pay a lot of attention to no-cost and
low-cost things that can be done quickly that will allow for early actions
and some quick success.
3c. One line of action that is sometimes left on the cutting
room floor is the idea of helping create new, or support existing, local
parallel efforts. Many states have a well developed set of local councils,
commissions and trusts who are natural partners in any effort to turn a
statewide curve. The relationship with these bodies should be about finding
common interests and partnering as equals on curves of mutual interest.
4. What would it take? Finally, there is another way to
frame the "turn the curve" challenge. In the "normal" turn
the curve process we ask "what works" to turn the curve as a way to
generate a shopping list of ideas from which we later choose what to do. The
more powerful question, however, is "what would it take?" "What
would it take to significantly reduce child abuse or teen pregnancy or raise the
rates of school readiness or school success?" The best analogies for this
type of question come from the successful effort to invade Normandy in 1944 or
land on the moon in 1969. This question is much tougher than taking on
incremental progress, but it may be a perspective that top leadership should consider. Incremental progress, however it is ultimately constructed, may be
more readily achieved in the context of a powerful vision for the future that
can come from answering this kind of question.
The population role
February 1, 2010
It is often true that
conversations within the Education community focus so intently on school
performance improvement that it is difficult to have a conversation about the
Population Accountability dimension of education. This problem is compounded by
the fact that many important education measures (such as graduation rate or
percent reading at grade level) double for population indicators. (See Chapter 5
of "Trying Hard Is Not Good Enough.")
So what is the population conversation we should have when it comes to
education? I think it is about why we need education in the first place, about
the role of education in our society. So why do we need education? The
answer has not always been obvious. (It would be interesting to revisit here the
work of Noah Webster.) Public education has been such a long accepted part of
our society that the basic need for education is rarely questioned. But when we
think about first purposes, it seems that education's role is arguably about (at
things: (1) creating good citizens and a civil society, (2) helping young people
reach their potential and become happy, productive, contributing adults, and (3) creating our next
generation work force and securing our economic future. Each of these three
roles lends itself to measurement. (For example, the adult literacy rate or the
percentage of young adults in work or education. And in each case, the education system could
be clearly seen as one of many partners with a role to play.
Part of the reason I think this conversation is worth having, particularly for
those immersed in the day to day management of K-12 (primary/secondary) system, is that it shows
that the education system is not responsible for curing the ills of the world.
There is such a long history of expecting just this from educators that we
forget how unfair that expectation is. By stepping back and thinking about the
role of education in society we have a chance to get back to our shared values, to
remember why our large monetary investments in education are worth every cent
and more, and maybe to begin to re-conceptualize education as more than a set of
services but rather a community responsibility for which everyone has something
Shortcut method for
choosing population indicators
Posting #5 January 24, 2010
method presented in on pages 54 to 56 of "Trying Hard Is Not Good
Enough" involves rating each potential measure "high, medium or
low" on three criteria: Communication Power, Proxy Power and Data Power. A
simpler method for doing this mirrors the selection steps in choosing
performance measures in steps 4 and 5 of Appendix G.
For each potential
indicator, identify those for which you currently have good data. Put a circle
next to these measures. Then ask "If you had to stand up in a public place
and explain to your neighbors what you mean by (the result in question, e.g.
Healthy Children), and could only use one of the measures with a circle next to
it, which one would you use?" Then ask, "What if you could have a
second.... a third?" Through this method you identify the top three
indicators for any given result. This method is exactly equivalent to the
Communication/Proxy/Data method for this reason. By first identifying the
measures for which you have good data, you address Data Power. In asking which
one people would use in a public place, it forces them to consider Communication
and Proxy power together, namely, which measures are most powerful that people
will understand? This method is faster and easier to use than the process of
rating each measure.
This method also sets
up the creation of a Data Development Agenda. Again, paralleling the performance
process, ask "If we could buy one of the measures for which we don't have
data, which would be the first we would buy?" "What if we could buy a
second?" Through this process you can create a prioritized list of needed
new and better data.
10, 2009 7:20 AM
found it an immensely useful seminar and I left feeling most excited about
RBA and its potential in a NZ social service context. I have had the
privilege of presenting it a number of times.
But ... alas
... I seem to have encountered a bit of a hitch. My colleagues and I can't
agree on how to make the most of some of the quadrants, and with some of
the things we have presented, we have confused those we are supposed to be
training. Can you help please?
I've had a look at the RA
Guide, and it seems to support one position, but we can't understand how
it actually fits.
We are looking at the Quadrant model,
particularly the Upper Right Quadrant.
The fact that it is
an upper quadrant means that it is concerned with our effort, the things
that we do. So if, in the Upper Left Quadrant we have among our activities
listed there the fact that we are delivering services to 12 families, we
could put in the Upper Right Quadrant information about the fact that our
staff have relevant qualifications, are up-to-date with their service
standards, deliver services in a timely manner, etc. All these things give
us an indication of the quality of our effort. It tells us that we have
gone to the most appropriate lengths to get the job done to best effect.
what about survey forms or questionnaires about the quality of our
service? These do not appear to be things that relate to what we do, but
what our customers feel about what we have done. Should these go in the
And if we were running courses, would the
details around the number of people completing the course go in the Upper
Right or the Lower Right? We can't agree. Some of us say it should go in
the Upper Right as the fact that X customers completed the course tell us
how well we did the work. However, others among us are saying that the
number of people completing the course is an effect and should go in the
Lower Quadrants--it relates more to the effect of our actions than the
effort of our actions.
IN the RAG, section 3.8, number
(5)(c), we are having difficulty understanding why a "circumstance
where numbers get better, but customers are not better off" would go
in the Upper Right Quadrant? Wouldn't this still go in the Lower right,
but indicate the level to which someone is better off? It just doesn't
seem to fit in an "effort" quadrant.
Sorry for the
lengthy pleas for help, but can you be of assistance?
Regional Relationship Manager
Family and Community
Ministry of Social Development
Andrew and Castle Streets, Dunedin 9016
PO Box 297, Dunedin 9054
are categorized on the basis of what question they answer.
Posting #4 September 10, 2009
(See prompting email)
The upper right quadrant "How well did we do it" category can contain
measures about customers. Consider the measures % of classes delivered on time
and % of customers who say classes were delivered on time. They are almost
identical measures. Customer data can often tell us how well services were
delivered (How well did we do it?). The fundamental question to ask when
thinking about whether a customer measure is upper or lower right quadrant is
this: Could we do well on this measure and customers might still not be better
off? For example, the % of customers who think the class is delivered on time is
95%. But the class itself is terrible and no one learns anything.
This same principle is illustrated by how we categorize the completion rate for
a service or training course. The mere completion of a service or training
course usually tells us little or nothing about whether people got anything
positive out of it. So % of clients completing service or training is usually an
upper right quadrant measure. But there are exceptions to this rule. If the
training has an established reputation for giving its students new skills, then
completion can be a lower right quadrant measure. Life saving courses, where
earning a certificate really means something, is a good example.
This principle can be carried further to the general question of how to classify
different measures of customer satisfaction. Customer satisfaction measures fall
into two broad categories: Did we treat you well? and Did we help you with your
problems? Customers can say they were treated well, that they liked the
counselor, thought the building was comfortable, accessible etc. but still not
be helped with their problems. So "Did we treat you well" is an upper
right measure and "Did we help you with your problems" is lower right.
The deepest underlying principle here is that measures are classified not on the
basis of some intrinsic characteristic of the measure, but rather on the basis
of what question the measure helps to answer. If measures help answer How well
did we do it? they go in the upper right quadrant. If measures help answer Is
anyone better off? they in the lower right. If they could conceivably answer
both questions, then pick the stronger answer, or as a last resort put it in
both places. This same principle applies to the difference between population
indicators and performance measures. Sometimes a given measure can play both
roles, so that sometimes it serves as a performance measure, and sometimes as an
I would encourage you to read Chapter 4 (especially pages 65 to 79 and 99) of
"Trying Hard Is Not Good Enough" where these matters are discussed.
There can sometimes be legitimate differences of opinion about how to categorize
a measure. When this happens, just put is somewhere and move on. Because all the
measures in both upper right and lower right quadrants will be considered in
Step 4 of the 5 step process for identifying the most important performance
measures (See Appendix G).
Finally, the reference to "circumstance" is specifically about the
client or customer's circumstance. Are they in stable housing?. Do they have a
living wage job? It is not about a more general definition of circumstances. For
this reason it always goes in the lower right quadrant?
Results Culture Change
Posting #3 September 9,
People talk about
culture change the way they talk about magic. We know this wonderful
transformation is needed and will somehow happen, but we're not sure how.
Let's take a shot at a definition of organizational culture. Organizational
culture is the range of accepted norms of for what people in an organization
think and how they act. An organization might have a dominant culture and
numerous subcultures. Subcultures might vary by program, profession, or
organizational role. Organizational culture also includes a story line or
mythology about why the norms exist the way they do.
Culture change then is any significant variation in or deviation from
organizational culture or subculture. Culture change can be positive or
negative. Sustained culture change is any culture change that survives some
defined degree of turnover in key positions. It is worth noting that culture
change is not a smooth transition. There are holdouts. Some parts of the
organization go ahead of others. Some people never get it.
It is arguable that there are three elements needed for culture change to take
place. This is a kind of hypothesis that might be tested with regard to creating
a results culture.
1. Leadership: No culture change happens without leadership. It may be possible
to talk about the evolution of organizational culture without leadership
direction. But any form of deliberate change requires leadership.
2. Vision and small steps: Culture change requires the odd combination of vision
and small steps. First, a vision of what the organization culture should be,
that is a picture of destination. Deliberate or directed change also requires a
well defined series of small steps that can begin the process and move it
forward. Massive overhauls are often not practical and usually don't work. So
culture change requires a pathway of small steps that lead to bigger change. One
guide to these small steps is the RBA Self Assessment Questionnaire new version
(available on resultsaccountability.com). Start with one supervisor identifying
and using performance measures. Then two supervisors, and so forth. After the
accumulation of enough small steps, it is possible to reach a tipping point
where change happens much more rapidly. It is worth noting here that among the
seemingly small steps to take is the change in forms and formats for strategic
plans, budgets, RFP's and contracts. Forms are the skeleton of any organizations
culture. They can live for decades. And if you can change them the change can
last for decades.
3. Finally, feedback. Any change process requires a feedback loop to see if you
are making progress. Two types of feedback are needed. Information is needed on
the extent of implementation. One can use the RBA Self Assessment Questionnaire
to calculate a score on the extent of implementation. The second type of
feedback is on whether curves are turning on key measures.
someone who helps manage the overall strategic planning process within a
UK local government context (children's services), I am currently
grappling with what you have called 'the wrong question'. This is in the
context of trying to support the establishment of an 'in-house' funder/contractor
relationship in line with the drive for UK local government to become,
first and foremost, a commissioner rather than simply a provider of public
While I appreciate that the final arbiter of a
successful strategy would be the population outcome indicator curves,
could it not be argued that performance measures, which after all have
been chosen following partnership deliberation of what works, act as a
useful 'working proxy' of strategy success?
In other words,
if performance measure curves are turning, could it not then be reasonably
assumed that, in due course, partners could expect to see turns in
indicator curves? I suppose this is similar to the notion of performance
measures acting as 'lead' indicators, with outcome indicators as 'lag'
Of course, if, in the event, the one does not
follow the other (i.e. if improved performance on selected measures does
not impact on population outcomes as initially hypothesized), then the
suitability of one or other of the individual components of the strategy
is clearly brought into question, and the proxy value of one or other of
the performance measures invalidated.
Am I missing something,
or is it a case of not so much 'the wrong question' as perhaps a
'yet-to-be validated answer'?
the success of population level strategies
Posting #2 August 21,
The general population
level progression from results to indicators to baselines, story, partners, what
works and strategies, often leads people to ask next, "What performance
measures will tell us if our strategies are working?" This, of course, is
the wrong question. To tell whether our population level strategies are working,
we must look to see if the indicator curves are turning. Indicators measure the
extent to which strategies are working. Performance measures tell us if the
individual components of our strategies are working.
For example, a partnership might come together to promote community safety as
measured by indicators such as the crime rate or the percentage of people who
feel safe. After working through the RBA/OBA process, they might settle on an
initial three part strategy which includes community policing, improved lighting
and a neighborhood watch program. To see if the overall strategy is working, we
would look to see if the curves are turning on the selected indicators (i.e.
crime rate and percentage who feel safe). As for performance, we would take each
component of the strategy in turn and identify performance measures for that
component. So for the neighborhood watch program, we might look at the
percentage of neighbors signed up, or the crime rate for neighbors in the
program compared to neighbors not in the program.
There is one other kind of performance measure relevant here, which may be the
source of some of the confusion on this subject. For those managing the overall
strategic planning process, there is a need to know the extent to which the
strategy (or strategies) have been implemented, and how well they have been
implemented. So a performance measure for the partnership managing the strategy
might be the percentage of agreed action steps that are on track. Notice how
this measure tells us how well the partnership is working, not how well the
overall strategy is working. One could easily have a strategy that is
implemented beautifully, but has no effect on the indicator baselines.
September 15, 2009:
And more....Having re-read your initial note: Does it follow that successful
performance of strategy components is a predictor of strategy success? And if
not does this mean that they are the wrong components?
of phrasing this question is, "Could all components of a strategy succeed
and the overall strategy fail?" I think the answer is "yes."
We might be doing the right things but not enough of them.
might be doing the right things and yet the strategy is incomplete. I believe we
have learned that strategies sufficient to turn population level curves require
the contribution of many partners, and include no-cost and low-cost elements,
some of which may be unusually difficult to assess. In addition, successful
strategies must be sustained over time and must include a process (an ethos?)
for continuous rethinking and improvement.
In both of these cases,
successful performance measures of strategy components would not be a good
predictor of the success of the overall strategy to turn a curve.
does not mean that partnerships responsible for developing such strategies do
not have a responsibility to track component performance, to spur performance
improvement and where necessary to redirect investments.
have such a long history of settling for the appearance and not the reality of
change in quality of life for children and families. In looking for intermediate
measures, we must be careful not to repeat this mistake in another guise. The
improved performance of individual services and even whole service systems would
indeed bode well for the quality of life of the customers of those services or
systems. But these improvements could well take place in the context of overall
deterioration in the well-being of the whole population of children. This is a
simple summary of the whole history of child protection reform. We fix problems
with services for abused children, but more children are abused.
Generation Contracting - Key Provisions
Posting #1 August 15, 2009
People have been asking
me for more detail on what I mean by "next generation" contacting (or
commissioning as it is sometimes called in the UK). Here are some additional
thoughts. I welcome your comments and suggestions.
Next generation contracts will have three essential provisions, and an optional
fourth. Provision 1
(Most important performance measures) and 2 (Continuous improvement process) are
sometimes used in present generation contracts, but these two with the addition
of provision 3 (Performance partnership between funder and contractor) create
the "next generation" funder / contractor relationship. Provision 4,
having to do with simplifying and standardizing contractor reporting, is a
highly desirable but optional component. Clearly there are many other components
of a complete contract genome (see Dawkins) that are necessary to have a fully
functioning contract, so these are necessarily parts of a larger whole.
1. Most important performance measures (Provision 1) specifies the most
important 3 to 5 How well did we do it? (Upper right quadrant) and Is anyone
better off? (Lower right quadrant) measures by which the contractor's
performance including its effectiveness on behalf of customers can be judged. If
these measures are not identified in the contract itself, the contract should
specify a process for quickly agreeing on the measures, with possible reference
to the RBA 5 step process in Appendix G of the RBA book.
2. Continuous improvement process (Provision 2) specifies that the contractor
will use a continuous improvement process (the RBA 7 Questions are naturally
recommended) to monitor and improve performance over time. The contract must
specify that this process takes place (usually monthly) at the highest level of
overall contractor performance (usually agency or major program level) but
should also, if possible, specify that the RBA 7 questions will be used (or
phased in) to every supervisory relationship.
3. Performance partnership between funder and contractor (Provision 3) specifies
that the funder and contractor will meet periodically (most likely quarterly) to
jointly assess performance on the 3 to 5 measures, the story behind the
baselines for these measures, and what each party can do to improve performance
in the coming period. These meetings should be preceded by the submission of a
performance report in RBA format (See Wyoming Part II and San Mateo budget
formats) from the contractor to the funder. In these meetings, the funder and
contractor act as co-equal partners in helping facilitate improvement. This
means that the funder will also agree to tasks that can help the contractor
improve, such as providing technical assistance, working to break barriers the
contractor may be experiencing in getting access to necessary resources or
cooperation from other agencies, essentially anything within the funder's means
that can materially support the contractor's performance improvement. Nothing in
this provision lessens the funder's usual responsibility for oversight of the
contractor's performance and use of funds. Nothing in this provision substitutes
for the grantee's ongoing improvement process in Provision 2 nor for the
contractor's responsibility to pro-actively solve its own problems without the
4. Coordination with other funders (Provision 4) - optional - The funder agrees
to actively pursue agreement with other funders who also purchase services from
the contractor for the purpose of simplifying and standardizing contractor
These are conceptual descriptions of the contract provisions and must, of
course, be translated into actual contract language. Suggested language or
examples of such language are welcome.
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