Chapter 1
Defining trust
Does my business have a trust gap?
We need trust for society to function, but in recent years numerous surveys have charted an erosion of trust in businesses, governments and societies.
What do we mean by trust? We mean a business’s intentions – its willingness to do the right thing, for example – as well the actions it takes to demonstrate this intention. Trust is both perception and action.
Trust can be embedded into products and services from the outset, rather than taking a reactive and remedial approach … to support greater stakeholder confidence and trust.
One of the many measures of public trust is the Edelman Trust Barometer, an annual report that asks people whether institutions are doing the right thing and how competent they are. In the 2020 Edelman Trust Barometer, business was rated the most competent institution; charities and non-governmental organizations (NGOs) the most ethical.
What was sobering, and this was pre COVID-19, was that no institution was seen as both ethical and competent. This matters because as trust erodes, trust gaps are emerging between what is possible through data and technology and what people will allow – slowing development of new business models and throwing growth opportunities into question.
Trust as a new disruptor
Until now, technology has been a major disruptor. It has created new ways of living and working, reshaped markets and enabled the growth of connected ecosystems.
But now trust is becoming the new disruptor.
According to the 2020 Edelman Trust Barometer, the public thinks technology is moving ahead too fast (61%). They worry about fake news and videos making it harder to distinguish between truth and lies (66%). People also fear that regulators cannot do their job effectively (61%), given their understanding of emerging technologies and the pace of change.
Accelerated change
61%of respondents to the 2020 Edelman Trust Barometer say the pace of change in technology is too fast.
Alternate reality
66%of respondents worry that technology will make it impossible to know if what people are seeing and hearing is real.
Antiquated regulation
61%of respondents say government does not understand emerging technologies enough to regulate them effectively.
Business leaders are also concerned. For example, in a recent CEO study by EY, cybersecurity and AI’s use of data and ethics rated in the top five risks facing companies.
What this confirms is that many people aren’t willing to accept technologies unless they can exercise more control over their outcomes. Added to the lack of timely and globally consistent regulation, this trust gap is a major challenge for businesses.
In light of these growing concerns, it’s important to look at your trust balance in its entirety.
Mapping your trust balance
To start, it’s worth recognizing there are many manifestations of risk that are related to trust. The most obvious and visible ones are probably data security, data privacy and technology. But look below the tip of the iceberg, and there is much, much more.
Mapping these risks holistically requires assessing them across several dimensions:
- Strategic: the impact on your reputation, business potential, societal influence and overall competitiveness
- Operational: the impact on how you run your organization, business processes, technologies and data
- Financial: the impact on your business performance, as well as current and future value
- Regulatory: the impact on compliance with standards, policies and laws
Managing these risks and understanding your trust balance should be a business priority. Getting this foundation right is the starting point for strengthening your competitiveness.
Chapter 2
The trust advantage
Why closing trust gaps will improve your business
The upside to getting trust right is competitive advantage. If you are more trusted than your competitors, you're more likely to grow faster. Your productivity will be higher. Your employees will be more engaged. Your customers will be more satisfied. It’s a virtuous cycle.
As shown in a recent EY study, consumers could move an estimated US$11.3 trillion in financial assets to more trusted financial institutions over the next five years.
Meanwhile, every business needs to become an intelligent enterprise that is sensitive to its environment – acting, learning, connecting and innovating. This will improve business performance in a multitude of ways:
- Gaining near real-time visibility into customers, markets, ecosystems, processes and finances, and uncovering new insights for the organization
- Prioritizing actions and accelerating decision making, close to the point of impact
- Understanding, anticipating and preparing for the future, proactively and accurately through proprietary data and insights
- Networking at scale, connecting people and data across internal and external functions, increasing coordination and reducing inefficiencies
- Discovering new sources of value and improving speed to innovation through insights
Once this is in place, enterprises will be able to trust the intelligence within their organization and harness the undeniable power of data and intelligent technologies, ultimately positioning them for sustainable, long-term value creation.
Chapter 3
Laying the foundation
How to build Trusted Intelligence
To avoid unintended consequences, enterprises must learn to harness the power and speed of intelligent technologies and the huge volumes of data they consume. In recent years, stories of the uncontrolled use of the data and technology have abounded; here are just three examples:
- A broadcaster that displayed voting totals of 110% in referendums
- Credit card algorithms that show bias against female card applicants
- Facial recognition software that misidentified professional athletes as criminals
So how can this be remedied? Embedding trust into an enterprise that gets its data from multiple sources and uses it multiple ways is a major challenge facing many organizations today.
To establish and sustain trust, an AI system must perform to stakeholder expectations with transparency and explainability; it must be secure, resilient, and unbiased.
What’s needed is a holistic approach, a way of moving from the general concept of trust into a distinctive trait that your organization can apply and master: Trusted Intelligence.
One way to do this is to think about your organization through the lens of an intelligent value chain, which balances trust across all aspects of the organization (value creation, business model, intelligence, data and advanced technologies).
How does this work? Let’s look at a few examples.
Consider current approaches to which data your employees can access. Traditionally, access controls were assigned depending on the role performed within the company. For example, HR employees have access to payroll, tax and pension data; those in the customer function could access customer databases, etc. This is usually referred to as role-based access controls (RBAC).
A more sophisticated approach is called attribute-based access control (ABAC), which specifies which types of data employees can access based on their role and the context, such as location, task and time. So instead of all HR employees having blanket access to payroll, tax and pension data, certain roles would be able to access the data they needed only when taxes needed to be calculated, or pension contributions needed to be reported or during salary reviews. Access may be granted only during working hours, for example, and only for employees located in the same country.
Think of it as the difference between walking into the kitchen and having free access to the entire room and every appliance in it, versus only the ingredients you need for a specific recipe along with the cooker and fridge for the specific amount of time required to cook dinner. You give people access to what they need, to do the task they’ve been assigned.
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Although ABAC takes time to configure and deploy, the pay-off is extra layers of security and trust. More refined access helps to protect the data, ensuring that its use remains with the parameters of agreed data policies, that any restrictions on data are respected, and prevents accidental misuse of data. Employees can access the data they need to perform their jobs: no more and no less.
We covered data controls; let’s now go back to the other parts of the intelligent value chain. Each part of the chain has perspectives to expand on. Some of these include:
- Building trust into business models:
Infusing risk thinking into business models and processes from the start can revolutionize a business’s approach to risk. By adopting a mindset of optimizing risks, trust can be embedded into products and services from the outset, rather than taking a reactive and remedial approach. “We use a proactive ‘Trust by Design’ approach to designing risk strategies, in order to support greater stakeholder confidence and trust,” says Amy Brachio, EY Global Business Consulting Leader.
- Building trust into AI’s use of data:
The transformative power of AI is high, but so are its risks. “To establish and sustain trust, an AI system must perform to stakeholder expectations with transparency and explainability, be secure, resilient, and unbiased. We developed EY’s Trusted AI Framework to infuse trust throughout the solution lifecycle, enabling AI practitioners to have the appropriate governance in place to design and implement a trusted system, and to continue to monitor its actions over time,” says Nigel Duffy, EY Global Artificial Intelligence Leader.
- Building trust into how data moves across your IT systems:
Many technology providers are investing in the new concept of “data fabric”: a virtual layer that sits atop data siloes and enables the secure ingestion, processing and adoption of data on a global basis. Organizations are directing their attention to this new frontier of data management to address excessive movement of data, duplication of datasets, inconsistent usage and poor quality of data and control protocols. “Technology at speed is a guiding principle we are adopting to drive innovation and performance. Having a trusted data fabric is a fundamental accelerator of our platform-based approach to advanced data management across our businesses, solutions and services,” says Nicola Morini Bianzino, EY Global Chief Technology Officer.
Embedding trust into how an organization captures, stores, uses and manages data is the starting point for Trusted Intelligence.
The importance of leadership
The power of Trusted Intelligence is that it helps businesses to thrive by embedding trust into data, advanced technologies and business models – enabling enterprises to harmonize the different elements of their business and create sustainable value.
Technology at speed is a guiding principle we are adopting to drive innovation and performance.
As the saying goes, it’s a journey, not a destination. Because once the foundation of Trusted Intelligence is in place, it requires agility to respond to ever-changing conditions, such as customer behavior and values, rising expectations, more data, evolving technologies and the emergence of new business models and business processes. The ongoing approach is one of balance and harmonization, because every element is important – not just the latest technologies or the biggest dataset. The harmony of the intelligent value chain is what positions the business for success.
As you can see, it is a multifaceted challenge, one that many businesses are facing. One that needs a strong vision from leadership and a clear execution program, as it also requires significant investment. And leadership cannot be delegated.
Questions for Boards and leadership to consider:
- What is our trust balance with customers – are we operating with a trust deficit or a surplus? What metrics do you have in place to track progress?
- Which elements of the intelligent value chain (value propositions, business models, data, technologies, intelligence) need attention now?
- What framework do we have in place to balance the elements of the intelligent value chain going forward?
Summary
An organization’s ability to create long-term value depends on harnessing the power of trust and data. But trust gaps have emerged with customers over unintended outcomes from technology and data. Closing these trust gaps is a business imperative.
Leaders need to map their current trust balance and use a model such as the intelligent value chain to build trust across the organization, for example into data access controls, business models, the organization’s use of AI and how data moves across IT systems. Only when this is a priority will organizations realize the competitive advantages of Trusted Intelligence.
