Hope is not a strategy
When James Cameron, world famous movie director, was starting the revolutionary AVATAR movie project he had t–shirts made up for his crew, with the words:
Hope is not a strategy.
This turns on its head conventional methods of training, which focus on knowledge transfer, and focus instead on simulating a relevant context, requiring teamwork, rapidly building levels of trust and understanding through self-directed learning.
Cameron is known for being particularly meticulous in his leadership style, he has a plan A, a plan B, and a plan C, and “expects to be on Plan C by his second cup of coffee.” It is for this reason that he has been asked to give lectures to NASA and the US Navy about how to manage complex and dangerous projects where devastating changes can happen in an instant.
Business decision makers are faced with taking action based on a set of ‘knowns’, and ‘unknowns’. Due to organisational pressures, time constraints and politics it is all too often the case that the ‘unknowns’ are rarely explored in great detail. Many leaders are operating against a highly complex, networked, and fast moving backdrop. They have no idea if their new ideas or strategies are going to be a success. All too often the actual results don’t live up to the initial business case.
One area that companies are placing big bets into the unknown is digital transformation, which will reach $2 trillion in global annual spend by 2022, at a growth rate of 16.7% a year. But according to Accenture, only 13% of executives believe they are getting top and bottom line growth from their digital investments, citing ‘talent readiness’ as the critical barrier to realising a return. For most large organisations, technology-led is the future. For many, the benefits are not being realised as fast as anticipated.
A new adoption model
Traditional models of adoption when it comes to technology in business have focused on the technology itself. As it turns out, our conception of adoption so far is that if the technology is a) useful enough, and b) easy enough to use, that this will create enough of a reason for an individual to start actually using it. In 1989 a theory called the Technology Acceptance Model (TAM) was created to show how the ‘perceived usefulness’ (PU) and ‘perceived ease of use’ (PEOU) of a product were the main determinants of the intention to use it, which in turn predicts ‘behavioural intention’ (BU).
However more recent studies have looked at the role of trust in this equation, to start to explain the human factors that impact the adoption of technology. One study called ‘Technology Acceptance Model with Trust’, looks at the attitudes of truck drivers to driver assist technology. In 2010, more than 61,000 large trucks were involved in fatal and injurious crashes in the United States, resulting in 3,675 fatalities and about 80,000 injuries (NHTSA, 2012). ‘Inattentive driving’ is the single biggest cause of these.
The adoption of this technology by drivers is crucial to reduce the number of road accidents. In-vehicle feedback systems have been proven to provide benefits in mitigating driver distraction. Research has shown that timely rear-end collision warning can reduce the number of collisions by around 80% for distracted drivers. Forward collision warnings have been shown to increase the average following distance maintained by truck drivers and help avoid 21% of rear-end crashes. The study took 100 commercial drivers, and measured their perceptions towards the technology, and correlated this to both their intention to use, and their actual use of the new systems. The role of ‘trust’ was found to be a significant part of the adoption equation, even more significant, for example, than the ‘ease of use’, indicating that we need to find ways of building trust and familiarity with new technologies and systems.
The best way to think of trust is like a prism, which can either channel or deflect actual use of the system depending on how the individual feels about it. Without it, adoption can be slow or even non existent. With it, adoption can be rapidly accelerated.
Creating $58M value by focusing on trust
In 2016 we met a client who had recently implemented an AI (Artificial Intelligence) based CRM system. Having invested millions in the customisation and implementation they rejoiced at completing the task and sat back to reap the rewards, but they never came. The sheer size of the organisation dictated that this first implementation was a trial for a much wider rollout. After months and months of internal comms, drilling home the reasons for the investment and a mandate from the CEO for all users to take action “or else”, there was still no sign of change.
We spent time with the steering group and the users to understand their opinions and objectives and it soon became clear that the major barriers to success were “motivation” and “trust”.
We designed a simulation to take the teams through a series of exercises that precisely replicated the business functions, financial levers and market dynamics. The experience demonstrated how each individual could influence the outcome and how trust in the system would improve their results. Knowing how and why they could contribute to the success of the programme motivated the team to approach things differently and within a few months the results started to show. Each team completing the experiential simulation achieved an average revenue increase of $100,000 per year. By the 3rd year the company had rolled out systems in 580 operating teams and through pre-emptive experiential engagement, had achieved a $58M increase in revenue as a result.
Training needs to shift from a hope strategy to a deliberate strategy.
It takes time for people to build trust and confidence. We need to approach this with a deliberate strategy, rather than hope that people will find their way, and adopt new things just because they ‘make sense’.
What we need is a ‘deliberate strategy’ where learners can experience the individual and collective emotions, frustrations, and consequences of using new technology, reinforcing desired behaviours and ways of working. This turns on its head conventional methods of training, which focus on knowledge transfer, and focus instead on simulating a relevant context, requiring teamwork, and rapidly building levels of trust and understanding through self-directed learning.
Trust is not a theory, or a thought, or an idea. It is built through personal experiences, that allow the individual to play out the reality for themselves.
What we need is a ‘deliberate strategy’ where learners can experience the individual and collective emotions, frustrations, and consequences of using new technology, reinforcing desired behaviours and ways of working.