Agile Diagnostics

Published:  17 September, 2017

Barnaby Donohew examines how the aftermarket can learn from the tech sector to improve diagnostic outcome

Giants such as Apple, PayPal and Google have driven a tech revolution that has impacted all our lives. They have successfully solved hugely complex problems to deliver products and services that have changed the world. Yet, still, they continue to adapt to satisfy shifting consumer demand and out-manoeuvre their competition.


Many of these players have now turned their sights on revolutionising the automotive industry. Rather than running for cover, we should learn from them and improve our own practices in anticipation of the impending technological onslaught; after all, our industry, and diagnostics in particular, is dominated by tech.


Of the tech sector’s many contributions to the world, I believe it is their business and working behaviours that we must adopt; specifically, their agility. In this context, agility is what it implies. It is the ability to be flexible, nimble and responsive to your customers’ needs and in the manner in which you provide solutions to those needs.


In fact, the word, agile, was originally appropriated by software developers to represent a set of principles guiding their work. It has since grown to include a culture and set of working practices that are being incorporated within many industries.


A problem shared
Has the tech sector always been agile? No. During the 1990s, as their complexity accelerated, software projects became increasingly risky undertakings; they frequently failed to launch and meet customer expectations, budgets, or timeframes. At the heart of the problem was uncertainty; their final forms could not be predicted up front, After all, not every problem or solution can be foreseen. The fact that customers were disengaged from the process only made it worse; they were frequently unaware of the impending failure of the work they themselves had commissioned.
In 2001, after realising the need for change, a group of software engineers came together to define an approach that would mitigate against the influence of uncertainty; they devised the ‘Agile Principles.’ You can see these here: agilemanifesto.org/ principles.html.


Their underlying philosophy is that developers should expect, embrace and manage change during the course of a project, be they changes in customer requirements, the nature of the problem, the development team, the business or those arising from other external forces. This software development problem should seem very familiar to any of us with diagnostic experience.
Can we predict the root cause fault at the beginning of a case? No. Do we know in advance all the tests we will conduct to determine a fault? No. Are we fully engaged with our customers throughout the diagnostic processes? It’s unlikely, even though we should expect our customer’s requirements to change during a diagnostic case.
This clear corollary between the worlds of software development and diagnostics has motivated me to adapt the agile principles to see how they might apply to us. I’ll introduce the adapted principles here but, be aware, this overview barely scratches the surface of how agile methodologies might help us.


Principles of Agile diagnostics
1. Our highest priority is to satisfy the customer through early and frequent delivery of diagnostic outcomes. We must continuously update our customers with our diagnostic observations (e.g. test results) and report which systems and components we have discriminated against. We should attach particular significance to the latter, as we can be more engaged with our customers if we discuss tangible concepts, such as physical parts.


2. Welcome changing requirements, even late in a case. Our customers do not have a single requirement equating to ‘fix my vehicle at any cost.’ Their requirements will be formed on the basis of a cost-benefit analysis, pitting the potential costs of diagnostics and repairs against the value of that vehicle. This value, influenced by the age, condition, and the perceived past, current and future utility and reliability, will change as the case progresses. It is also possible that a customer’s personal situation might change during a diagnostic case, e.g., they may have a change of economic circumstances. Therefore, we must expect, embrace and properly manage these changes.

3. Business people and workshop teams must work together throughout cases. Clear communication is essential if high first time fix rates and customer satisfaction levels are to be built and maintained. This requires all members of the business (whether workshop managers, or customer service representatives) to work together to ensure that diagnostic cases are well managed and their outcomes clearly delivered to customers.

4. Build diagnostic case-work around motivated individuals. Give them the environment and support they need, and trust them to get the job done. Motivated individuals will be determined to solve a diagnostic case and will be prepared to undertake the personal investment necessary to iterate themselves toward more efficient and effective practices. Supported and trusted individuals will be more motivated. It’s a win-win situation to uphold this principle.

5. The most efficient and effective method of conveying information to and within workshop teams is face-to-face conversation
Forget emails, messages (whether of the instant or post-it variety) and phone calls. Establish and maintain regular face to face contact across your business and with the customers.

6. Definitive diagnostic outcomes are the primary measure of progress. A diagnostic observation acts to increase or decrease the remaining ‘search-space’: i.e. it increases or decreases the set of components (candidates) that might contain the root cause fault; therefore, this diagnostic outcome, the search-space reduction, can be the only measure of progress within diagnostics.
Only a suitably designed diagnostics system could define a search-space and track its changes – at present, no such system exists.

7. The process should be sustainable. Excessive pressure and demands on a diagnostician’s physical and intellectual state are not sustainable. Diagnostics requires learning, action and reflection and diagnosticians should be afforded the appropriate time for each. Pressure to reduce any of these is unsustainable for both the diagnostician and the business.

8. Continuous attention to technical excellence and informed and accurate decision-making enhances agility. he acquisition and application of knowledge it is at the heart of agility. It is also central to diagnostics. In either case it’s a principle that we should always champion.

9. Simplicity – the art of maximising the amount of work not done – is essential. Is there a quicker or simpler, diagnostic test, which will provide an equivalent diagnostic outcome? If so, find it and use it.

10. The best diagnostic analyses emerge from self-organising teams. Structured teamwork does not exist within automotive workshops. It should. The development of a diagnostic team would increase the potential range of expertise,
maximising the likelihood of correct diagnostic decision-making. Practices such as paired diagnostics (two diagnosticians working simultaneously on the same case) and swarm diagnostics (the gathering of the whole diagnostic team to work on a case) should be strongly encouraged.


All teamwork has the benefits that it facilitates the transfer of knowledge amongst diagnosticians, increasing their effectiveness and reducing business risks, such as those arising from diagnostic roadblocks (difficult cases) and the loss of knowledge when a key staff member leaves. Furthermore, the resulting teamwork and learning promotes a happy and satisfied, and therefore more productive group of diagnosticians.


Members of a team should be able to select their own cases depending on their expertise and problem preferences (e.g. classed according to the initial symptoms) as their motivation, efficiency and effectiveness will remain high.

11. At regular intervals, the team reflects on how to become more effective, then tunes and adjusts its behaviour accordingly
Progress through an agile diagnostic case should be broken down in to a series of incremental steps, with each taking the form a repetitive three-phase learn-act-reflect cycle.


Each cycle should deliver a diagnostic outcome of value to the customer. Within the learning phase, the business should determine the customer’s requirements and the diagnosticians should increase their understanding of the problem before them and decide on their next actions. At the end of the cycle the business and diagnosticians should reflect on any new knowledge and what went well or what could have gone better. The reflective output should be fed back in to the learning phase of the next cycle, and so on.


Behaviour
The above principles may seem a little wishy-washy and it still may not be clear why they should be adopted. However, consider this: If you have made significant investments in equipment and training and found that your first time fix rates and customer satisfaction levels have not improved, then you will understand that there must be one remaining component in which you must invest; your behaviours. I strongly suggest you learn from the world-domination of tech sector businesses and make them agile behaviours.


Automotive Analytics Limited is producing a white-paper entitled ‘Agile diagnostics’, which fully explores diagnostic agility and its potential to revolutionise diagnostics. You will be able to download it for free by signing up at: http://automotiveanalytics.net/
agile-diagnostics


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