The 11 Principles of Trust - How to Create Business Value Through Trust

The 11 Principles of Trust
How to Create Business
Value Through Trust

Trust is a
universal concept
The 11 Principles of Trust 2

It applies
not only to
people,
places,
and things...

...but also to companies, products,
and services across all industries.

It’s particularly
relevant today for
technology and
software
companies.

Many of whom are under
increased scrutiny for their
data practices.

And because data has
become the lifeblood of
modern business...

…it’s critical that customers, partners
and regulators trust you to
protect their information.

Are there any software
companies that you would
voluntarily trust to protect your
most intimate personal details?

Do you actually trust them to
protect your information?

Or are their services so integral to your life
that you feel you have no other choice?

In fact, many of us have
resigned ourselves to
sharing data even though
we feel increasingly
uncomfortable about it.

Trust is particularly
important for
companies using
machine learning
and artificial
intelligence (AI).

It allows them to access
the data required to fuel
machine learning models.

However, AI also presents new
challenges for trust.

privacy,
security,
reliability,
bias, and
transparency.
In particular around

Heightened awareness of these issues
presents an opportunity for software
companies to differentiate on trust.

We believe that
customers will
increasingly
demand that
companies operate
fairly and
transparently.

In terms of how they
treat customers,
employees, and
partners...

…and society
as a whole…

The opportunity
is to use trust to
differentiate in
your market.

Our principles provide a
guide to building trust with
your customers.

But first, let’s define trust.

Trust is the balance between the
value that you deliver and the
comfort that customers experience
when interacting with your
company, brand and products.

Value is your core business
proposition – why customers
use your product.

Drivers of value include:
Improved forecasting and analytics
Improved product quality
Cost and time savings

Comfort is peace of
mind for your
customers — knowing
that using your
product won’t cause
problems for them.

Drivers of comfort include:
Reliability and stability
Responsible and secure data handling
Transparent business practices

When you provide value and comfort,
you’ll get happy customers who
promote your brand.

When value and
comfort are out of
sync, trust gets
eroded and
customers leave.

You can use the following
principles to increase trust in
your organization.

Create new value
through trust.
1 The 11 Principles of Trust 32

Avoid taking a
‘compliance is
enough’ approach.

Instead, look for opportunities to
create new value for your
customers and for the company.

Find out what your customers
value, and what it takes to make
them comfortable.

Then plan the steps to reach trust.
This will be your trust roadmap.

Customers that
trust you will share
more data, allowing
you to enhance
your products and
provide more value.

Build trust into
your culture.

Everyone should
understand how they
can help build trust,
starting at the top.

In particular,
responsibilities
around
customer data.

Communicate how
you handle data
clearly and publicly.

Design resilient
systems to reduce the
impact of an attack.

Breaches will happen,
so design your systems
to compartmentalize
damage from attackers.

Don’t just focus on
software systems, think
about business
processes that might be
attacked as well
(e.g. financial processes)

3 approaches have been shown to help:
The principle of least authority
Decentralization
Redundancy

Construct a rapid
remediation plan and
practice using it.

When a security or
privacy compromise is
discovered, follow your
well practiced incident
response plan.

And ensure you notify affected
customers immediately.

Providing timely remediation is
essential to protect your brand
and retain customer trust.

Effective plans
cover both the
common
scenarios and
outliers.

Understand customer
and regulatory
privacy requirements.

First, consider whether
you need personal or
other sensitive data to
deliver value.

Then assess your data sources,
including partners and suppliers.

And be mindful of how your
data management practices
can impact customers.

Adapt your approach to
meet the requirements
of different jurisdictions
as required.

Give customers
control and oversight
over their data.

Software companies have
traditionally assumed broad rights
through their privacy policies.

This approach is
no longer
compatible with
privacy legislation
or building trust.

Drive the conversation
on consent and
acknowledge that
ownership remains
with the customer.

Be transparent.
Give users visibility into the personal
data you’re capturing and storing, and
give them control over that data.

Encourage
engagement
through relevant,
timely prompts and
adjustable settings.

Root out bias.

Discrimination
in all forms is
under increasing
scrutiny.

Human bias and
algorithmic bias are
both challenges for
AI companies.

Reduce human bias by addressing
individual, team, and organizational
tendencies to act on judgment
alone, without using data.

Ask questions throughout the
development process to
reduce technological bias.

Problem definition:
are there groups who
could be unfairly impacted?

Collecting training data:
do sampling methods lead
to overrepresentation of
certain segments?

Model training:
can performance
be optimized for
each segment?

Ongoing:
does our governance
process account for
changes to input data
or model weights?

Develop a fair model
for value exchange.

Customers will
increasingly
gravitate towards
business models
that are
quantitatively and
qualitatively fair.

Think carefully about what you need
from your customers (e.g. data) and
what you will offer to your customers
in exchange (e.g. insights).

As relationships
deepen and you
collect more data,
ensure that you
provide more
value in return.

If customers are getting insufficient
value from the product, issues of
comfort will be more acute.

And trust will be eroded.

Make trust
measurable.

Set objectives for the value
and comfort you deliver for
each aspect of trust.

Track what you do,
what you achieve, and
your level of customer trust.

What you achieve
includes how
accurately models
perform and how
quickly customer
requests are
fulfilled.

Measure customer trust through
ROI case studies and surveys on
your trustworthiness.

Anticipate the
unexpected.

Things will go wrong.
When they do, make
sure you’re well-
positioned to minimize
the impact.

Threshold / upper limit
Track system performance
metrics and set thresholds to
quickly find the root cause.

Design systems
so they
automatically
enter recovery
mode and send
alerts when
thresholds are
exceeded.

Look at product
usage data and
customer feedback
to track and respond
to common issues.

Explain yourself.

Make your systems, policies,
procedures, and products
more explainable.

Start by understanding your
buyers’ and users’ expectations.

Use what you’ve learnt
to provide relevant
information in your
product to help your
users make decisions.

And finally,
communicate
your efforts to
customers and
partners.

Remember:
The questions surrounding AI are
complex, so revisit your thinking
and be prepared to discuss and
adapt your stance.

The 11 Principles of Trust:
Create new value through trust.
Build trust into your culture.
Design resilient systems to reduce
the impact of an attack.
Construct a rapid remediation plan
and practice using it.
Understand customer and regulatory
requirements.
Give customers control and oversight over
their data.
Root out bias.
Develop a fair model for value exchange.
Make trust measurable.
Anticipate the unexpected.
Explain yourself.
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Want to dive
in deeper?
Download our
11 Principles of Trust
white paper.

The 11 Principles of Trust - How to Create Business Value Through Trust

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