branding banks for shareholder value 3.0 customer perceptions
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Branding Banks for shareholder value Discussion Draft Section 3.0
1
© Geoffrey Johns 25 March 2010
Branding banks for
shareholder value
Section 3.0
How customer perceptions
develop
Planned series of papers
Discussion
Draft Version
Release
Date
Creating shareholder value - an outline 1.0 Mar-10
Knowing customers 2.0 Mar-10
How customer perceptions develop 3.0 Apr-10
Branding banks is vital
TBA
Branding banks is hard
TBA
Measuring customer perceptions
TBA
Gaps analysis
TBA
Bank structure and brand control
TBA
Six Sigma and brand control
TBA
Valuing bank brands
TBA
Branding Banks for shareholder value Discussion Draft Section 3.0
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© Geoffrey Johns 25 March 2010
Introduction
This is the third in series of discussion drafts in which I attempt to trace the path from
customer perceptions to shareholder value. The first covers shareholder value as a goal
of the system and the analysis framework I use. The second is about knowing
customers through segmenting on key characteristics. This section deals with
understanding how customer perceptions develop. This understanding is crucial if banks
are to have influence over how customers and non-customers think of their brands.
Section 1.0 contains the general introduction to this series of papers.
Personal experience trumps all other
messages
My first and perhaps most important observation about the development of perceptions
in banking is that personal experience is more important than any external influence. I
have interviewed more than one person still fuming about a bounced cheque twenty
years ago.
AdvertisingMediaPeers
The opinions of
trusted advisors,
colleagues, friends
and family are sought.
The media is scanned for
messages that confirm our
beliefs
Advertising communication
is accepted when it aligns
with favourable beliefs
Individual
The perceptions of the
individual largely
shaped by experience
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Banking is not top of mind in most people’s day to day lives. Adverse experiences,
sometimes trivial to those who design bank processes, can sear themselves into people’s
minds. An impression of a bank can settle itself in the heads of customers quite early in
their lives.
People screen out messages that do not gel with their preconception based on their
experience.. They interpret messages that are not screened out to reinforce their
preconceptions. They actively seek confirmation of their preconceptions in the
environment about them.
Own experience
Media comment
Trusted advice
Marketing communications
Contradiction
filtered
Confirmation
sought
Info
rma
tio
n
rein
terp
rete
d
Based on their experience customers construct stories in their heads where the elements
of the stories are self-reinforcing. They are slotted into a pattern of cause and effect in
which the customer justifies what is often a gut-feeling by a logic pattern imposed upon
it.
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© Geoffrey Johns 25 March 2010
Customers create stories in their heads about their bank. The exhibit below is developed
from some of the attributes that are measured by the TNS Business Finance Monitor in
Australiai. It shows how my qualitative research indicates that people construct stories
that explain their perceptions. Tight knots are formed in people’s minds in this way. ‘My
bank values me as a customer therefore they take the trouble to understand my
business therefore they are (are able to be) helpful and supportive’. Sometimes
researchers are concerned that statistically they are unable to distinguish the relative
importance of such attributes in driving satisfaction. I suspect that this in part caused
by the fact that attributes are rarely mutually independent. They are strung together in
stories.
They value me
as a business
customer
Understands my
business
Responsive and
flexible
Helpful and
supportive
Helps
businesses
achieve their
business goals
Primary
causality
Positive
feedback
The knot tightens until an experience is powerful enough to cut through it cuts through it.
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The process of disaffection is discontinuous
The following set of exhibits is taken from my qualitative research of the deterioration of
customer commitment in business banking. It illustrates the process of adverse
experience cutting the Gordian Knot of inertia.
I can’t rely on you
You don’t
value my business
You don’t
know me
I don’t trust
you
You are
exploiting me
You are a
danger to my business
Six steps to disaffection
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© Geoffrey Johns 25 March 2010
Each step requires its own impetus. At any stage it is possible with the right actions to arrest
decline. But it takes an enormous management effort to put the process into reverse; there is
a ratchet effect at work. To do this requires inculcating a whole new thinking framework into
the minds of customers. You have to reach beyond responses to new experiences to attitudes
and beyond attitudes to beliefs. It seems that we cannot easily retrace our steps. By contrast
each step prepares the customer for the next one. In the story the customer is telling in his or
her head the logic builds as each step is taken. „You don‟t value my business because you
don‟t know me‟.
On one occasion I was told, on joining a bank, that management consultants had estimated a
net defection rate among business customers of 9% pa. I believe that what arrested this in the
short run was mandating visits to customers by senior management to assure them their
business was valued. However, improvement in measured satisfaction took two years of
effort including integrated rebranding.
21
I can’t rely on
you
You don’t
know me
You don’t
value my business
I don’t trust
you
You are a
danger to my business
You are
exploiting me
Mutual lack of contact
Just being an account number
Untailored communications
„You don‟t know me‟ is a common early warning sign that that the situation is prone to
adverse surprises just around the corner
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© Geoffrey Johns 25 March 2010
22
I can’t rely on
you
You don’t
know me
You don’t
value my business
I don’t trust
you
You are a
danger to my business
You are
exploiting me
Lack of access to senior bankers
Seemingly arbitrary account management decisions
No proactive solutions
Indifferent service
Inflexible application of rules
„How can you value me if you don‟t know me?‟ Business people, at work are at the centre of
their world. Do they feel that they are peripheral at best to the world of their bank?
23
I can’t rely on
you
You don’t
know me
You don’t
value my business
I don’t trust
you
You are a
danger to my business
You are
exploiting me
Bank mistakes
Inconsistent policies
Poor processes
Gaps in product/service offerings
Bank actions hard to predict
Poor dispute resolution
Changes to management team
Inconvenient access
Not keeping up with the market
These things relate more
to poor management than
bad intentions Lack of banking skills
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© Geoffrey Johns 25 March 2010
It is important to understand that right up to this point the bank need not have done too much
wrong. In a later paper, I shall discuss the importance to brand of relationship managers. For
now I will say that a relationship can have reached this point without being revealed in any
Key Performance Indicators.
I can’t rely on
you
You don’t
know me
You don’t
value my business
I don’t trust
you
You are a
danger to my business
You are
exploiting me
Decisions based on bank
not customer needsThis is driven by a build up of
the previous three. If you don’t
know me and you don’t value
my business and I can’t rely on
you, then I don’t trust you.
Unprofessional
Media scandals
Bankers lacking
understanding of business
Poor performance vs. competitors
At this point, the bank is on the customer‟s „watch list‟. The bank, however, still might not
realise this. In terms of commitment, which I described in the last paper, the search for
alternatives is beginning.
I can’t rely on
you
You don’t
know me
You don’t
value my business
I don’t trust
you
You are a
danger to my business
You are
exploiting me
Aggressive pricing
This perception is
more easily triggered
if the four previous
perceptions are in
place.
Cost cutting
Reduced functionality
No support
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© Geoffrey Johns 25 March 2010
In the case uppermost in my mind is the case of Westpac Banking Corporation. In 1992
it came close to insolvency on the back of perhaps a dozen large property loan
delinquencies. Westpac’s management of its SME customers in the years leading into
the crisis had been among the best of banks. But at this point, increased pricing,
reduced lending, greater security demands, more rigid terms, conditions and covenants
were imposed on them. Sometimes relationship managers apologised to customers
explaining it was because of corporate lending gone bad. The key thing felt by
customers was that their account was being managed with no reference to or
understanding of their own business. They felt completely out of control of events vital
to them. On the spectrum of customer perceptions this is as bad as it gets.
26
I can’t rely on
you
You don’t
know me
You don’t
value my business
I don’t trust
you
You are a
danger to my business
You are
exploiting me
Arbitrary, irrational and
aggressive credit decisions
Major disruptions to business
processes
Fear of being at a significant
disadvantage to competitors that
have a better bank
The existence of the earlier perceptions
will mean that these issues are nearly impossible to resolve.
Many customers will have defected or at least moved some of their business before this
point is reached. One of the most common reasons I have heard for switching banks by
business customers is not so much that that the reality of the situation was a rock
bottom. It was more like they felt they ‘couldn’t live with themselves’ if they continued
to let their bank treat them this way.
Obviously, these same six steps don’t happen to every customer and some customers
are more or less tolerant. Nevertheless it is a fair take out from my qualitative research
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© Geoffrey Johns 25 March 2010
over many years. At each step the process becomes harder and less certain to reverse.
This is because the bank begins to be seen in the mind of the customer as ‘Well they
would do that, wouldn’t they, because that’s the people they are?’ In short it is a brand
killer.
Resistance to changing our minds
There are lags too in how we change our minds. I am not a psychologist but I offer the
exhibit below as a representation of how I think people test their perceptions in the
world of experience.
Beliefs
Attitudes(Reusable decisions)
Experience (feedback)
Choices
Outcomes
Contextualisationfeedback
Needs
Reframing feedback
Expectations
Realignmentfeedback
The key seems to me to be expectations. Up to a point outcomes will be evaluated to
confirm expectations rather than refute them. It is only when there is a rupture that a
process of accommodation to new experience begins. Changes in expectations can lead
to attitudes changing to contextualise the new experience. At this occurs before the
walls of belief can be breached. But then sometimes something that matters to the
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© Geoffrey Johns 25 March 2010
person happens so out of line with expectations that the result can be a sudden
reframing that is all the more powerful.
The Conversion Model explaining discontinuity
Let’s turn again to the Conversion model™ which I described in Section 2 of this series.
The process of which the Conversion model takes a snapshot in time is in fact dynamic
and ongoing.
As dissatisfaction grows the customer’s search for alternatives intensifies. At the same
time the customer’s perceived importance of the choice of bank is likely to grow. This is
generally considered to be a stable characteristic; some people innately think this is
more important than others. But it is also something that people rarely focus on. When
they need to think about who they bank with the importance of the decision tends to
increase.
As the customer evaluates alternatives to their bank and these are seen positively
dissatisfaction with the bank tends to increase. It may even be that the test alternatives
Dissatisfaction
Enhanced
perception of
alternativesIncreased
ambivalence
Increased
importance of
choice of bank
Lag
Lag
Lag
Adverse
experiences
Need for new
product /serviceLoss of
business
Lag
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© Geoffrey Johns 25 March 2010
to the extent of actually having dealings with them. They are likely to meet with other
bankers and to consult friends and business associatesii. The resulting increase in
disposition to alternatives and increasing dissatisfaction with their bank heightens their
level of ambivalence. Usually, what is then needed for the next step to be taken is a
new banking need. People relatively rarely switch banks altogether. There is more a
seepage as new needs arise.
The picture tends to be one of rising disaffection leading to a mental break with the bank
that may not be immediately apparent. The bank may not become aware until value
shifts. Even then, if value shifts on a new product the bank may still be unaware of the
relationship breakdown.
Customer inertia in banking
Much is said about customer inertia in banking. People tend to rarely move from one
bank to another. In Australian business banking the ‘churn’ is less than 5% a year and
of these, I guess that perhaps one and a half percentage points are pushed for reasons
of risk or under-pricing for riskiii. In personal and business banking value seeps rather
than switches. This usually happens when a new product is required or some life event
(e.g. moving to another employer or town) occurs. There are several reasons for inertia.
People have more important things to think about than banking. They tell themselves
that all banks are the same. They think that if their bank compares unfavourably in
some area (e.g. online banking) it will soon catch up. They tell themselves ‘if it isn’t
broke don’t fix it’. They have life routines they are reluctant to change. They have got
used to their bank and can predict how it will deal with them. There are lots of reasons
for inertia and some of them are based on good sense. In a later paper in this series I
shall offer a dollar quantification of its value to a bank. But strong as these ties are they
can mask, until it is too late deep underlying reasons for change.
The following exhibits draw some causal connections from a few qualitative studies I
have done that touch on inertia. There has been an event that cast some light on
inertia. As I say in Section 1.0 of this series there tend to be few breakthrough products
in banking. However online banking was an instance where the breakthrough in
customer needs was significant and where banks did not move simultaneously or with
equal competence. The key events were roughly these. Banks offered some form of
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© Geoffrey Johns 25 March 2010
electronic banking first to corporate customers and then to the SME market. This was
because the customers were valuable and had a strong need. Next, online banking was
offered to the personal market. There were economies of scale in development and
reduced transaction costs. Development activity was channelled into the personal
market. Meanwhile business online banking increasingly seemed out of date and clunky
as customers compared it to their personal banking experience. Also business
customers had often experience of dealing with more than one bank online and could
make comparisons. Banks therefore began to reassign ICT resources to the business
market but they were not all able to do this immediately. The illustration below
describes the logic of inertia.
Business customers are reluctant to change their
banking arrangements
The service element of a new product is difficult
to evaluate in advance of purchase
Often any changes are hard to reverse if they don’t work
outThere can be a
high opportunity cost in diverting effort from the
core business to banking issues
‘If it aint broke don’t fix it’ -
people learn to live with minor defects and work around
There is a belief among businesses that all banks are
the same
There are cogent reasons why customers are reluctant to change banks as shown in the
exhibit above. Especially customers are reluctant to shift their transaction accounts as
illustrated in the exhibit below.
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© Geoffrey Johns 25 March 2010
Transaction accounts are important to
business people and very sticky to shift
Day to day cash flow management is the life blood of
business
Often cash flows are unpredictable
and volatile – many businesses are living on the
edge
An overdraft facility is highly
prized by businesses but
tightly controlled by banks. Without
one, cash flow control is of vital
importance
Transaction accounts are
complicated and messy to switch
from bank to bank
Transaction accounts carry
with them risks of fraud and default
A window of opportunity opened and then closed again as laggard banks caught up but
not before some loss of value.
Business customers are
reluctant to change their banking arrangements
It takes a seismic shift to create opportunity to
switch customers to new products
On-line / internet banking has
irresistible appeal to many
businesses
A window of opportunity
opened
The window of opportunity closed again
as inertia reasserted
itself
First movers have many advantages
even with less than perfect products
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© Geoffrey Johns 25 March 2010
I see this as an example of a situation favouring customer inertia suddenly becoming
more liquid but then refreezing. What loosening of inertia we can expect to see in
banking is most likely to come from ICT developments or from financial crises. I see
these as always being temporary followed by the reassertion of inertia.
Kano analysis and its implications for
measurement
Around 1980, Noriaki Kanoiv threw a sizeable spanner into the works of measuring
satisfaction. In doing so he adds another layer of complexity to my analysis.
22Actual needs fulfilment
Perc
eiv
ed
satisfa
ction
Neither satisfied nor dissatisfied
Kano distinguished between the varied ways in which different aspects of a product or
service cause our satisfaction level to respond in different ways. In the exhibit above
the green line shows satisfaction to rise in line with the extent to which we perceive our
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© Geoffrey Johns 25 March 2010
needs to be met. This can be considered the norm. The more you meet customer needs
the happier they are.
Actual needs fufilment
Perc
eiv
ed
satisfa
ction
But in other aspects of the product or service there are some things (the orange line in
the exhibit above) that are expected. Customers are not satisfied when they are well
performed but become angry when they fail. A while back I worked with a firm that
provided pension funds with administrative service such as filing financial statements
and also high level tax and investment advice. Failure to lodge financial statements with
the supervisory authorities on time could result in fines for the fund trustees. These
expected parts of the service if they were unfulfilled would leave their clients highly
dissatisfied. Correspondingly those parts of the service that were intended to add value
the supported funds and which could have delighted their clients would never get off the
ground in their clients’ perceptions.
Kano analysis also identifies elements of the product or service that delight customers.
They are not expected and are all the more powerful in their effect. As an example
there is the relationship manager I knew who drove out to the airport at night to
personally deliver a replacement MasterCard to a client about to board a plane.
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© Geoffrey Johns 25 March 2010
There are some important implications for measuring satisfaction. The first is that you
cannot simply add up or average the ratings of a number of attributes where some are
expected, some are normal and some ‘delight’, in Kano’s termsv. They are different and
in a sense exist on different scales measuring quite different things. Moreover, they are
connected. Failure in an expected part of the product or service can lead to a completely
different view of performance in a ‘delight’ factor. In effect this means that a group of
customers that were distinct in that a bank had failed them on the expected factors
when compared to a group of customers where this was not so would have given
different ratings to the delight factors. The implication of this is that, for example, to
derive customer ratings of attribute importance statistically as opposed to customer
stated importance can be misleadingvi.
An experimental retro-fit of Kano analysis
Sadly, I have never been asked by a client to conduct a Kano analysis. Were I to do this
it should ascertain the Kano classification of attributes by a qualitative study, ideally
supported by a quantitative study before the main study. However, Gary Lembit
(already recognised in Section 2.0 of this series) and I did attempt to assess how Kano
analysis might reinterpret an analysis of the business banking sector. I am aware that
such a retro-fit after the event is, in multiple ways unsatisfactory but, nevertheless, i
found the results interesting and will share them with you here.
The attributes listed below are similar to but not identical with those used in the TNS
Business Finance Monitor cited in Section 2.0. We then classified them according to
Kano analysis as sown in the table below. We used a separate classification for price
because, candidly, we didn’t know where to put it.
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© Geoffrey Johns 25 March 2010
Pricing Expected Satisfiers Delighters
a Understands my future needs
b Flexible solutions
c Recognition for my business
d Provides ideas on financial management
e Understands my business and history
f Outcome adds value to my business
g Responds quickly
h Knowledge and expertise
i Offers sound advice
j Helps me avoid risks
k Comprehensive product range
l Value for money
m Prepared to negotiate
n Accurate
o Access to specialists
p Efficient branch network
q Latest electronic services
r Easy to use systems
s Competitive pricing
Next, using the results of the work already completed. We created a matrix of scores
given for each attribute against statistically derived importance. Note here my earlier
caveat concerning statistically derived importance. Here we had no option, of course.
The matrix below shows the outcomes. The data points are cloud coded:
Pricing
Expected
Satisfiers
Delighters
Pricing as might be expected fall into the low performance quadrant but it is also the low
importance quadrant. Customers didn’t like it but it did not matter to them that muchvii.
The high performance / low importance quadrant contain nearly all the ‘expected’ (the
satisfier) attributes. As Kano would predict, they were done well but this was not seen
as important. Kano would also predict that they would become important if they were
done badly but our data didn’t give us a data point to verify this with.
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© Geoffrey Johns 25 March 2010
26
a. Understands my future needs
b. Flexible solutions
c. Recognition for my business
d. Provides ideas on f inancial management
e. Understands my business and history
f. Outcome adds value to my business
g. Responds quickly
h. Knowledge and expertise
i. Offers sound advice
j. Helps me avoid risks
k. Comprehensive product range
l. Value for money
m. Prepared to negotiate
n. Accurate
o. Access to specialists
p. Eff icient branch network
q. Latest electronic services
r. Easy to use systems
s. Competitive pricing
LOW PERFORMANCE
LOW IMPORTANCE
HIGH PERFORMANCE
LOW IMPORTANCE
LOW PERFORMANCE
HIGH IMPORTANCE
HIGH PERFORMANCE
HIGH IMPORTANCE
o
j ih
f edc
ba
s
m l
rqp n
k
g
In the low performance / high importance quadrant we find most of the ‘delighters’ they
unexpected features that come as a nice surprise to the customer. Customers are
responding to the survey with – ‘yeah that would be good – I don’t get it though’.
Finally, the ‘satisfiers’ the routine things that are part of the expected service fall in the
high performance / high importance quadrant. This is doing well at getting the basics
right.
Overall, while I am fully aware this is by no means a definitive study on the application
of Kano, I do believe that it offers a strong suggestion that Kano analysis does have
something important to say. It should be deployed more often in banking studies.
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© Geoffrey Johns 25 March 2010
Lags in management response
I have talked about lags in terms of the how people respond to their experiences. Lagsviii
also occur in how banks respond to customer disaffection. Chief Executives in banking
talk often about it being like changing course on an ocean liner.
2006 2010
2007 2008 2009
2006
Recognise problem
2007
decide what to do
2007
prepare inplementation
2008
Implement
2008
New regime operating
2009
most clients experience improvement
2009
all clients experience improvement
2010
results noticeable in surveys
2006
Problem occurs
The exhibit above is based on my experience of major change programmes in a couple
of banks. It is of course illustrative. If anything I think it understates the time lag. It
also assumes that the change is successful. This isn’t always the case.
Measurable client responsiveness to improvement in the business system lags for several
reasons. First, even improvements can have adverse short term consequences. From
about 2003 all Australian banks began to improve the incidence of relationship
management. Generally smaller portfolios lead to greater customer satisfaction and
eventually commitment. However, in the short term several adverse consequences
arise:
Some customers must be moved to the portfolios of new managers. If the
average portfolio size is being reduced from 100 to 80 this means 20% of them.
Qualitative research shows customers rarely like this and the results can be
expected to show in surveys.
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© Geoffrey Johns 25 March 2010
Some relationship managers are promoted prematurely and find trouble finding
their feet. Some customers can be expected to perceive deterioration in service
because of this.
Some managers are new hires from outside the bank and they take time to learn
how the system works. Some of them may not be good recruitments anyway.
The management style among the next tier of managers has to change this
transition if quite difficult as senior managers have to become more hands onix.
Times of change often involve new initiatives coming at front line managers from
different directions. For example if the Chief Risk Officer wants portfolios cleaned
up at the same time as the sort of initiative I have described above the difficult of
change management is compounded. Similarly, new front line ICT systems may
be introduced.
Customers can interpret good intentions unkindly, especially if they tend already
to disaffection. Increased intensity of account management meant to strengthen
relationships can easily be seen a intended to promote tighter risk control.
Going beyond the unintended adverse consequences of improvement there are other
reason why change seems slow to achieve results:
Customers take a while to become aware that a change has occurred. Customer
reviews are often infrequentx.
New customer needs are often infrequent so the satisfaction experience by a
product / service need being well handled takes a while to come through as does
the financial measurement of the sale.
Let me conclude this discussion with a vignette from my own experiencexi that illustrates
a couple of the point made above.
At one time I was closely involved in a major switch towards relationship
management. I ensured through direct mail that each customer knew who
their relationship manager was, how to contact them and what their role
was i.e. to solve customer problem. Meanwhile the branch network was
also undergoing change as part of the same overriding initiative. One
outcome intended or otherwise was that the branch network was shifting
its focus away from small business towards home mortgage lending. It’s
amazing what changing objectives and rewards can do in a well-disciplined
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© Geoffrey Johns 25 March 2010
work force. So newly appointed relationship managers were inundated
with complaints, questions and problems connected with branch service
over which they had no control. I was inundated by complaints from
relationship managers! All of this was pretty much unforeseen and all of it
was completely unavoidable within the commonly accepted world view of
the organisation.
So lags, discontinuity and volatility are natural to the system and we have a new system
element to consider. I illustrate this below.
Management tampers with the system
The system displays unpredicted lags and volatility
LagLag
I am fairly certain that I witnessed more than one purposeful management change that
would have succeeded had the corporate suite shown more patience and wisdom. In the
words of one top executive I have known.
If they (divisional heads) can’t do it we’ll find someone (management
consultants) to help them and if they still can’t do we’ll find someone who
can!
Well good luck! I should say. Because that process takes about three years in my
experience and that’s time you never have.
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The word ‘tampering’ in the exhibit above, I have taken from Edwards Demingxii. To
quote him at greater length:
We may now formulate two sources of loss from confusion of special causes
with common causes of variation:
1. Ascribe a variation or a mistake to a special cause when in fact the
cause belongs to the system (common cause);
2. Ascribe a variation or a mistake to the system (common causes)
when in fact the cause was special.
Over-adjustment is a common example of mistake No. 1. Never doing
anything to find a special cause is a common example of mistake No. 2.
To my mind this is one of the most profound statements on the subject of management
that has ever been made. I have, in this paper described a number of sources of
variation in the development of customer perceptions of a bank. How management
respond to these in business system design can bring the system under control or can
exacerbate the volatility. In responding to perceptual feedback to management change
making the wrong choices great damage can be done to brands as I shall discuss in the
forthcoming section on brands and bank structures.
The exhibit below outlines some of the connections between the models I have used in
this paper.
Business and personal customers
Most of my illustrations above have been taken from business rather than personal
banking. That is where the majority of experience has been. I should say that my view
is that personal banking displays much the same behaviour except that it is more muted.
I can tell you that almost exactly two thirds of business customers (from a Business
Finance Monitor sample of over 10,000 respondents) rated the importance of the
banking relationship as a 1 or 2 on a scale of 1to 5 where 1 means very important. I
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© Geoffrey Johns 25 March 2010
don’t know what the figure for personal banking is but I’d guess slightly lower. The
comments I have made above I think would also be true for personal bank customers
but perhaps somewhat muted.
Where should we look for signs of sea change?
I have argued that management failure to detect improvement in response to
investment can lead to vacillation. What then can be done? First measuring process at
a detailed level helps. Also it helps to measure activity and responses rather than only
financial outcomes.
For the Conversion Model I should look at three key transitions illustrated below.
Entrenched
committed
Average
committedShallow Convertible Available Ambivalent
Weakly
unavailable
Strongly
unavailable
Committed Uncommitted Open Unavailable
Customers Non- customers
1 2
3
I would expect to see early signs coming in roughly the sequence shown. It doesn’t
have to be in that order. But you do need to dig for signs quite deep in the detail of
whatever data you have.
Next I should look at the attitudinal group we identified in section 2.0 that we then called
leaders. Their perceptions of change may be more acute than the mass of customers.
Therefore you might see changes in their commitment presaging that of customers as a
whole. This follows a line of thinking that I was introduce to by Eric von Hippelxiii In
Appendix 1, I reproduce my 2006 outline of how to deploy von Hippel’s ideas in research
for innovation. They apply as much to understanding response to brand.
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The role of brand
What then is the role of brand in customer perceptions?
A major theme of this paper has been that perceptions are strongly based on personal
experience. Marketing communications are seen as have a weaker role. I shall discuss
how such communication can be made effective later in this series of papers.
Customer expectations
Customer perception of
the experience
The objective quality of the experience
BRAND
I want to conclude this present section, however, by suggesting that a key role of
banking brands is to modify the customer’s interpretation of experience. This is
achieved by a cyclical process through which expectations themselves are modified.
The secret of life is honesty and fair dealing; if you can fake that, you've
got it made. Groucho Marx
But, alas, contrary to the view of Mr Marx, it can’t be faked.
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A tentative overview of this section
Own experience
Media comment
Trusted advice
Marketing communications
Contradiction
filtered
Confirmation sought
Info
rma
tion
rein
terp
rete
d
They value me as a business
customer
Understands my
business
Responsive and
flexible
Helpful and
supportive
Helps businesses
achieve their
business goals
Primary
causality
Positive feedback
I can’t rely on you
You don’t
value my business
You don’t
know me
I don’t trust
you
You are
exploiting me
You are a
danger to my business
Six steps to disaffection
Beliefs
Attitudes(Reusable decisions)
Experience (feedback)
Choices
Outcomes
Contextualisationfeedback
Needs
Reframing feedback
Expectations
Realignmentfeedback
Business customers
are reluctant to change
their
banking arrangement
s
The service element of a new
product is difficult to evaluate in advance of purchase
Often any changes are hard to reverse if they don’t work out
There can be a high opportunity cost in diverting effort from the
core business to banking issues
‘If it aint broke don’t fix it’ -
people learn to live with minor
defects and work around
There is a belief among
businesses that all banks are the
same
Actual needs fufilment
Perc
eiv
ed
satisf
act
ion
2006 2010
2007 2008 2009
2006
Recognise problem
2007
decide what to do
2007
prepare inplementation
2008
Implement
2008
New regime operating
2009
most clients experience improvement
2009
all clients experience improvement
2010
results noticeable in surveys
2006
Problem occurs
Management tampers with the system
The system displays unpredicted lags and volatility
LagLag
Entrenched
committed
Average
committedShallow Convertible Available Ambivalent
Weakly
unavailable
Strongly
unavailable
Committed Uncommitted Open Unavailable
Customers Non- customers
1 2
3
Customer expectations
Customer perception of
the experience
The objective quality of the experience
BRAND
People create logic to justify the outcome of experience
It takes powerful experiences to change beliefs
There are cogent reason for inertia
There are hurdles to changing beliefs
Inertia is overcome
Minds are changed
The bank responds
Measurement is hard
But evidence can be inconclusive
Leading to floundering
A brand that conditions experience.....
Could reinforce good and mitigate bad experience
Summary and conclusions
A main theme of this series of papers is that branding banks can only be attempted
through a consistent pattern of decisions taken throughout the organisation at a process
level of detail. In the first paper in this series I argued that:
shareholder value should be the goal of the system;
process design should take into account measurement of how changes in
customer perception affect shareholder value; and
this can occur through disciplined process design in a systems context.
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© Geoffrey Johns 25 March 2010
In the second paper, I argued that:
customer’s should be managed as ‘segments of one’;
customer behaviour, commitment and value should be independently measured
by systematic but flexible segmentation strategies;
commitment, as defined by the Conversion Model™, is the primary measure of
customer satisfaction that should be used by a bank;
In this paper, I describe how:
personal experience if the main driver of perception of a bank;
customer banking behaviour is affected by discontinuities in their perceptions that
are sometimes difficult to understand, measure and predict; and
these discontinuities are caused by breaking inertia in the mindsets of customers.
management response can easily allow the natural variation in perceptions of the
brand;
My conclusion is that this kind of issue is inevitably part of the nature of banking
unless deeply held mental models are changed. Part of the purpose of this series of
papers is to contribute towards that change.
In the next paper in this series I shall focus on brand itself and why effective
branding is essential for banks.
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Appendix 1
Research for Innovation Geoffrey Johns January 2003
"Business has only two basic functions: marketing and innovation.
Marketing and innovation produce results. All the rest are costs."
Peter Drucker
Does Market Research have a Part to Play in Innovation?
We often hear of successful product innovations that took place without any market
research. Akio Morita, The Chairman of Sony, is quoted as saying that the Walkman
would never have been launched had they relied on market research. Probably, this
would go for many other product innovations from fax machines to mobile 'phones.
Nobody saw the need until they were out there in the market.
The magazine "Fast Company" tells the stories of many firms with "skunk works" or
"chief ideas officers". Mostly, they work towards innovation from an understanding of
the developing capabilities of technology. Firms try to generate as many viable projects
as possible while limiting the role of users in development to the sifting and evaluation
technology process. Indeed this is how the market research is traditionally seen in the
product development cycle.
The exhibit below sets out a traditional view of the product development cycle. Users
are traditionally involved in the testing stage. Once a prototype has been developed,
potential users evaluate it. This has some sense to it. It is difficult, in many cases, for
existing users to predict how they will react to circumstances that are barely on the
radar screen. For example, 1970s users of landline telephones would not readily have
predicted text messaging.
OPPORTUNITY
IDENTIFICATION
Market definition
Idea generation
DESIGN
Consumer
measurement
Perceptual
mapping
Product positioning
Forecast sales
Marketing mix
INTRODUCTION
Launch planning
Tracking the launch
TESTING
Advertising and
product testing
Pretest market
forecasting
Test marketing
PROFIT
MANAGEMENT
Decision support
system
Market response
analysis
Innovation at
maturity
Profit portfolio
Management
The product development
cycle(Source: Urban and Hauser)
Traditional
customer
involvement
Innovative
customer
involvement
Innovative
customer
involvement
Professor Eric Von Hippel‟s
commentary
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How then can market research help managers in the innovation process? The answer, or
part of the answer, lies in lead user research.
Lead User Research
Lead users (sometimes called "lead steers" because they are the people who both
predict and guide the movement of the "herd lead the followers towards new concepts
and ways of meeting their needs. Lead User research was pioneered by Eric von Hippel,
Professor of Technology at the MIT Sloan School of Management in 1986. I have
developed this work for use as a market research tool that offers a systematic approach
to innovation.
This is not the only approach for every business. Some businesses will launch many
products and invest in developing the ones that work. Others will watch the success of
smaller and nimbler competitors and buy the ones that succeed. Still others will bet the
business on a single bright idea. Having said that, the approach we describe in this
paper should be considered by many businesses. This is especially of businesses that
have a powerful brand that must be nurtured. They have less scope for constant
experimentation. It is also true of complex, multifaceted businesses where the
management functions of control and coordination make a freewheeling corporate
culture harder to integrate.
Who are lead users and why do they matter?
The Exhibit below is based on Everett Rogers' conceptual illustration of the diffusion of
an innovation in the marketplace (Diffusion of Innovations 1995). To Rogers' diffusion
segments I have added Von Hippel's concept of Lead Users. It is important to
understand that Lead Users differ from Early Adopters in important ways. An Early
Adopted will see an innovation and think "Yes, that's for me!" A lead User, however, has
already begun to develop the product in his or her own mind. Indeed often they will
have developed a prototype or perhaps a "work around" solution to their needs. The key
fact about a Lead User is that their need for a solution is so great that they have already
begun to imagine solutions. They have "one foot in the future" already. Note: it is the
need that matters more than they specific solution. But it should be a need that can be
articulated so strongly that the passage towards the solution becomes almost seamless.
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Lead users matter for two reasons:
What they want today Early Adopters may want tomorrow and the Mass Market the
day after; and
They can help us build a viable solution.
Often we can survey the traditional market broadly and find that a big majority are quite
happy with what they have now. The trick is to home in on those that demand
something more.
Why not ask all users what they need?
Most importantly because they don't know. They great majority of people cannot
imagine the products and services that they will require in the future. In research
studies, people will mostly try to be helpful. However, they will think within the box of
what they get now. If they articulate requirements at all it is along the lines of - the
same but faster, cheaper, better. That road leads to commoditisation and trench
warfare against competitors trying their hardest to do pretty much the same.
Shortly, we will describe how to discover Lead Users and deploy their skill and
understanding. Before this, however, we must introduce the concept of "commitment"
based on TNS's proprietary methodology The Conversion Model™.
Time
Adoption
Lead
users
Early
adopters
Mass
market
(followers)Laggards
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Introducing Commitment Segments into the Innovation Research Model
Do Lead Users tell the whole story? No, not if we want to understand the rate of take up
of the new offering. Understanding the needs of Lead Users can help us design a
product. However, financial evaluation requires that we make some estimate of the
spread from the small number of Lead Users to Early Adopters and from them to the
Mass Market. The rate of take up is crucial. Rogers' stylised adoption curve shown
above is only a generalisation of the experience of some typical markets. In any given
case we know little about how take up might spread from Lead Users to Early Adopters
and from them to the Mass Market. We need to understand the responses of committed
and uncommitted customers to measure and manage take up.
Commitment is a concept used in the TNS Conversion Model. This is a methodology
used to measure the shift in customers between alternative brands and products. In this
model a committed customer is one that:
is satisfied with the brand they use at present;
does not rate alternative brands highly;
show no ambivalence between brands; and
is involved in the decision, in that it matters to them which brand to choose.
The exhibit below illustrates the segments into which we group a brand's customers and
non-customers according to their commitment. While we usually focus on brands we
have also analysed other aspects of a category, for example, various distribution
channels. Two questions are relevant here.
If users want the innovation, do they want it from your brand? And
How quickly will take up spread from more to less committed customers.
Committed -
entenched
Committed -
average
Uncommitted -
shallow
Uncommitted
convertible
Strongly
unavailable
Weakly
unavailableAmbivalentAvailable
Customers
Non customers
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© Geoffrey Johns 25 March 2010
A committed customer is more likely to:
stay with the brand longer;
be less price sensitive;
buy more of the brand's product / service set; and
be more aware of and give more consideration to the brands marketing
communications.
For our present purpose, a committed customer is more likely to accept an innovative
product.
In the present context, therefore committed customers are more likely to accept the new
product offering. Moreover, they are more likely to accept the new product offering
under the brand under consideration. We need to include both high committed and
uncommitted customers in our focus groups. Committed customers are likely to be early
adopters of the proposed products but may be unrepresentative of other customers. By
using the Conversion Model to segment existing and potential customers by their level of
commitment, we can better predict rates of take up.
Committed followers will
be influenced by
commited leaders. The
rate of penetration will
depend on the leaders'
span of influence
If this group accepts the
concept they will be the
earliest adopters
Uncommitted followers
are likely to be laggards
Acceptance by
committed leaders will
allow some penetration
of uncommitted leaders.
The rate of penetration
will depend on the
strength of the offering
LeadersFollowers
Un
co
mm
itte
dC
om
mitte
d
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© Geoffrey Johns 25 March 2010
Each of the groups illustrated above will have a different rate of "take up". Each will be
influenced by the others. To get a better view of the rate of take up, we need to
understand the unique perceptions and behaviour of each.
Digging deeper into rates of take-up
I have developed a conceptual model to help us organise research information about the
commitment segments. The framework is shown in the exhibit below.
Attractors are factors that draw users towards an innovation. They can include, for
example:
Superiority over existing offerings.
Fit with lifestyle, aspirations, self-image.
Repellers are factors that drive users away from an offering. They can include, for
example:
Perceived risk.
Switching costs, including time, money and perceptions of sunk costs.
Triggers are factors that can prompt adoption. They can include for example, for
example:
Opportunities to trial.
Behaviour
Attractors
Repellers
Triggers Enablers
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© Geoffrey Johns 25 March 2010
Opportunities to observe successful users.
Enablers are things that must be available to the potential user for them to adopt the
innovation. For, example, in the case of on-line banking, these include ready access to
an Internet connected PC.
Research into this adoption model fleshes out the drivers behind the commitment
segments and allows take up rates to be modelled more effectively. The forces we
describe above are not necessarily objective reality. We are concerned only with the
users perception of them.
The search for Lead Users
How do we select the sample? There is no one answer for every study. We need to
redefine the selection criteria a little differently each time. As a guide, however, Lead
Users meet the following criteria. They are:
Successful.
Respected by their peers.
Opinion formers.
Good networkers.
Sophisticated users of products in the category in question.
Early adopters of new products.
able to think outside the square.
people who seem to have one foot in the future already.
demanding and driving clients.
And, for business users. also
highly in touch with the needs of their own clients (where they are businesses).
committed to their own success and the growth of their businesses.
people who are building an organisation rather than just running a business.
But, above all else, what we are truly seeking are users who:
Have needs that foreshadow general demand - that is to say they are pushing the
envelope of what the existing products offer them.
Expect to get high benefit from solving those needs so they are inclined to invest
their time, energy and money in innovative solutions.
“It was something I needed at my work” Tim Berners-Lee
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© Geoffrey Johns 25 March 2010
We don't have to find too many of them. A dozen or so is often enough to work with in
the design stage. But we do have to find the dozen that best meet the above criteria.
True Lead Users are different from early adopters. Early Adopters see something on
offer and want it sooner than the bulk of the market. Lead Users want something they
cannot yet see, taste or feel. They only know that they have an unfulfilled need. We
may not always be able to identify people who match this description in every market.
However, our methodology is designed to get us as close as we can.
How do we find Lead Users within a client's customer database?
Where there is a detailed customer database or a good relationship management system
we can often work with our clients' front-line staff to identify Lead Users. This process
requires highly disciplined management. However, with a small amount of training and
good communications material and check-lists, this approach can work well.
Among the criteria for being a Lead User are not things like being friendly and easy to
get on with. As a matter of fact Lead Users are more likely to complain a lot and make
nuisances of themselves. Being a pain to deal with is almost a key requisite.
Often relationship managers will be asked to nominate some of their least liked clients.
How do we find lead users where users / potential users are hard to identify?
There are several approaches to the problem of finding lead users where individual users
are hard to identify. This occurs, for example in situations such as fast moving
consumer goods or communications media.
Approaches can include:
Getting Lead Users to self-select, for example by responding to a competition.
Selecting from certain groups likely to contain potential lead users of the innovation.
For example, this might include the audiences of art-house cinemas for developing
an avant-garde magazine.
Using large samples for initial screening.
Selecting from among access panels of people who have been engaged in other
research projects relating to the category.
Telephone screening
However the initial group are selected, the next stage is telephone screening. We
generally only need to ask a few questions like:
What do you see as the two or three main forces that will affect your business over
the next few years?
What do you see as the two or three main forces affecting the employee relations
over the next few years?
What do you see as the two or three main forces affecting the economy over the next
few years?
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However, the actual questions we do ask will differ from assignment to assignment.
Designing these questions is a critical success factor.
The focus groups
The next stage is to hold focus groups, perhaps more accurately described as
"workshops" to design the innovation.
The focus groups should not be too large. If we have the right participants we have to
ensure they get enough "elbow room" to have their say. Four people is perhaps the
ideal number but three is enough, providing the selection process is rigorous. Five is
getting close to too many.
We would advise holding several such focus groups. It is easy to go off on a tangent
unless the direction is confirmed. Ideally, there will also be control groups of people who
do not meet the criteria of being Lead Users. This serves to highlight the unique
perspective of the Lead User groups.
The focus group methodology
It is important that the workshops are more than just a brainstorming or discussion. We
need the discipline of a pre-designed methodology.
One that works well is derived from the Quality Management Technique known as
"Quality Functional Deployment" (QFD) (in a somewhat clumsy translation from the
original Japanese) or "the House of Quality" after the shape of the diagram often
associated with it. Note: we are not advocating a full implementation of QFD. Even if
that were the main focus, it would be necessary to adapt the methodology to the unique
needs of the situation. However, it is not the main focus. The focus is to elicit the needs
of Lead Users who foreshadow the needs of the broader market. However, we need to
ensure that the methodological disciple is in place from the outset to ensure there is a
path in place towards business model design.
QFD is designed to closely relate product features - conceived by the organisation - to
product benefits sought by customers.
Its key strengths are:
It provides a direct and explicit link between market research and business decisions.
It allows assumptions about the market to be surfaced and tested.
It allows people with different functional specialisations, such as marketing and
technical teams, to work together within a common framework.
It can be layered to provide detailed design, for example of information systems, to
be "nested" within broader design parameters.
It supports concurrent development and hence fast-tracks innovation.
The diagram below illustrates the assembly of matrices used in QFD.
OPPORTUNITY
IDENTIFICATION
Market definition
Idea generation
DESIGN
Consumer
measurement
Perceptual
mapping
Product positioning
Forecast sales
Marketing mix
INTRODUCTION
Launch planning
Tracking the launch
TESTING
Advertising and
product testing
Pretest market
forecasting
Test marketing
PROFIT
MANAGEMENT
Decision support
system
Market response
analysis
Innovation at
maturity
Profit portfolio
Management
The product developmentcycle
(Source: Urban and Hauser)
Traditional
customer
involvement
Innovative
customer
involvement
Innovative
customer
involvement
Dr Eric Von Hippel‟s commentary
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© Geoffrey Johns 25 March 2010
How is the QFD methodology applied?
The process itself is straightforward but facilitation is demanding.
1. The focus groups are used to elicit and measure the benefits sought by users. Note
that the market research should be specifically designed with its use for QFD in mind.
2. The planning matrix is used to weight the benefits to be offered with particular
reference to competing offerings.
3. The business response comprises the array of product features conceived by the
organisation in response to the benefits sought by customers.
4. The impact analysis evaluates each product service feature in terms of its effect on
delivering customer benefits.
5. The response priorities quantify the importance of each feature of the design.
6. Finally, the response correlations evaluate any cross-impacts, desirable or
undesirable among the product features.
Customer
benefits
Planning
matrix
Business
response
Impact
analysis
Response
correlations
Response
priorities
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© Geoffrey Johns 25 March 2010
The same technique can be used to go into more detail. If this is required, the response
priorities of the first exercise become the customer benefits of the next and so on.
QFD is best carried out as interplay between research, "backroom" analysis and
workshops among the organisational stakeholders. If the right customer research is
carried out all of this can be done within the organisation. However, some organisations
have benefited by directly involving customers in the process.
The methodology can be painstakingly detailed or broad brush. Generally in the
Research for Innovation context we err on the side of keeping things short and simple
when working with Lead Users. However, the approach in any situation has to be
dependent on the circumstances. To some extent the methodology has to be
reinvented for every application. TNS work with client sponsors to determine the right
solution for them.
Involving the "Home Team"
By "Home Team" we mean the client staff who will be responsible for designing and
selling the innovation. Ideally, the "home team" will work jointly with Lead Users at
some stage during the workshops. They will be able to suggest some organisational
responses to the benefits customers seek and test with the participating customers
directly the extent to which these might meet their needs.
Note: the "home team" generally requires preparatory work before involvement in
workshops. Part of this training is concerned with the QFD workshop. However, just as
important is the development of the Home Teams' understanding of the strategic
context.
The "out of the box team"
The "home team" is there to respond to Lead User needs and test that response with the
Lead Users. While they will be responding to customers with leading edge needs, it is
rare that their responses will be of themselves innovative. It is more likely that they will
be extensions of or rearrangements to what has gone before.
An organisation seeking innovative solutions must do more. One solution is a separate
"out of the box" team. This team will observe the interaction between the "home team"
and customers and develop challenges to the solutions reached. These challenges can
be used later in management forums to test for truly innovative solutions. The "out of
the box" team should be chosen for a broad management perspective and independence
from traditional organisation streams and products.
We mention above the need for the "Home Team" do approach the issue with a prior
understanding of strategic context. This is even more important for the "Out of the Box
Team". In the final section, we will discuss an approach to this.
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© Geoffrey Johns 25 March 2010
Creating the strategic Context
In the case of an innovation that is relatively minor in the context of an organisation's
overall activities this may be unnecessary of may just involve dusting off an existing
strategic plan.. however, when the innovation is at the level of the business model, it is
vital.
There are a number of possible approaches. Which is best depends on the issue at hand
and the culture and capability of the organisation. The approach we describe below is
based on Future Scenario Planning. We find it to be a well-documented methodology
that meets most needs.
Future Scenario Planning
Future Scenario Planning meets our purpose precisely because it is not an attempt to
predict the future. Rather is intended to open the minds of the participants to several,
equally plausible scenarios. These may not cover every possible outcome. There is no
need for that. The chief benefit and one that fully meets the needs of Research for
Innovation is to prepare the organisation to be fully receptive of and alert to the needs
of Lead Users. The outcome that matter is in the innovation design not in the scenarios.
These are merely stepping stones towards the goal.
In this context, the approach is over one or more workshops. Both the "Home Team"
and the "Out of the Box Team" should participate although it is somewhat more relevant
to the latter group. Ideally, it should be held about a week before the QFD sessions.
The content of the workshop(s) is, typically:
QFD
Lead Users Home Team
Needs Capability
“Out of the Box” Team
Strategic Context
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© Geoffrey Johns 25 March 2010
Identify the key drivers of change affecting the brand and category. These include
social, eco-systemic, political and regulatory, technological, economic and industry
trends.
Group these by common root causes and common high level impacts into
manageable "packages".
Assign ratings to each package by importance and uncertainty.
Work on the highly uncertain drivers (those for which the outcome is a "spin of a
coin") to create several different scenarios. Four is a good number of scenarios with
which to work.
Tell the stories of the scenarios from the first pebbles to the avalanche through the
process of change to the outcomes.
Set the innovation plan in the context of the scenarios. Ask what elements might
work or fail under each scenario.
The organisation should now be ready to make the best use of its Lead Users to outpace
its competitors.
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Notes to Section 3.0
i Described in Section 2.0
ii All the evidence we have leads me to think accountants have a crucial role in this. I
shall discuss this further when I look at brand audiences in more detail.
iii I have put this to several bankers without having any dispute but I expect few people
know for sure.
iv Kano, Noriaki (ed.) (1996). Guide to TQM in Service Industries. Tokyo: Asian
Productivity Organization. ISBN 978-9283311300.
v Actually I understand there are no completely satisfactory translations the terms Kano
uses. Expected, delight, satisfiers, dissatisfiers are fairly commonly used and seem ok to
me.
vi This is related to and compounded by my assertion, earlier in this paper that
attributes are not mutually exclusive because customers link them together in mental
stories.
vii Low importance attributed by customers to pricing is a theme that runs through
banking that i shall discuss in a later paper
viii Lags are one of the key features of systems including business systems. The other
main features are feedback loops. Together these lead to the adverse consequences of
the management decisions happening someplace else, some time else to someone else.
(I don’t know who said that originally).
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© Geoffrey Johns 25 March 2010
ix For reasons I shall explain in detail in a later section
x I have frequently interviewed customers who were unaware that they had a
relationship manager. Also I have interviewed customers who thought they had one but
did not.
xi Here from a while ago is a record of my personal experience. The measure is a
amalgamation of business customers perception of bank competence, trustworthiness
and support. The new business model was introduced around January 1993. There was
a decline for three years before the improvements were recognised by customers. The
rise thereafter was swift to overtake National Australia as the leading bank on this
measure. Source: Financial Products Review Group
xii .Out of Crisis’, W. Edwards Deming, 1980 Cambridge University Press, ISBN 0-521-
30553-5
xiii Toolkits for User Innovation: Eric von Hippel, Lead User, Configuration System,
Creativity Techniques, Open Innovation by Lambert M. Surhone, Miriam T. Timpledon,
and Susan F. Marseken
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