The first step in improving anything is to understand the current situation. To do this you need accurate, timely data about what is actually happening on the frontlines of field service.

The principle of value stream mapping, which comes from the discipline of lean manufacturing, is a useful concept to help guide this step. Your goal in analysing the current situation is to identify value - as defined by your customers’ needs - and then to map the value stream, which is all of the steps and processes that you undertake to deliver that value. Then you can look for bottlenecks, so you can eliminate any wasteful steps. In addition, if there is data missing, you can identify ways to fill the gaps.

The analysis requires data. In recent years, many field service operations have undergone some degree of digital transformation, which for many has meant that they have gone from having limited data about field service - knowing just whether the job was done, and the customer had paid - to having too much data that they can’t analyse or make sense of. Not only is there mobile data that tracks field service technicians’ whereabouts, and progress on any task, and gathers feedback from customers, but there is also a wealth of internal data such as from ERP or CRM systems, financial data, call centre information, repair data and customer emails. Combined with data about parts and assets, some of which comes directly from IoT enabled equipment, you end up with a complex mix of structured and unstructured data, which is often hard to makes sense of.

The most effective way to identify patterns in the data is to use data science techniques such as machine learning.

For example, using machine learning in the analysis of asset and parts data enables you to take a structured approach to asset lifecycle management. If you can spot patterns in repairs and revisits, you can start to predict and prevent failures. Again, generic tools can make some headway here, but field service specific tools have algorithms that have been programmed with field service knowledge which are better at surfacing genuine opportunities.

There was a time when in many businesses, the service operation was viewed as a cost centre, a necessary, but expensive, functional department.

This view is outdated; today, companies understand that field service is integral to the business. Field service technicians are not only the face of the brand, they are able to build relationships with customers and have opportunities to generate revenues through cross selling and upselling.

In the same way, there is a growing recognition that field operations goals need to be integrated with wider organisational goals. The opportunities identified in step one need to be prioritised based on a number of factors: which can easily be actioned, which have the greatest improvement potential, which offer the greatest return on investment, which are the low hanging fruit. But overarching all of this is the need for opportunities to align with overall company goals.

Furthermore, at this stage, there is a need to understand what the ROI of change will be, and to quantify the risk of not changing. If you can put a financial value on your goals, it will help you to make the business case for the investments you will need to make, both directly in terms of expenditure on the technology to drive change, and indirectly in terms of the time you will need to commit.

Once the current situation is analysed, opportunities to improve are surfaced, and goals set, aligned to the company strategy, you then need to decide how to act to meet those goals.

You are moving into the tactical stage of the seven-step process, and are focusing on practical actions that you and your team can take. The questions you need to answer at this stage are:

• What are the processes, practices, controls and levers that you can alter to influence performance?
• Which metrics that support these levers, need to move to indicate improvement?
• What are the thresholds for improvement - how much do the metrics have to move?

Once you have defined the metrics and set thresholds, you can use them to define employee KPIs, and you will be ready for the next challenge which is to change the behaviour of your employees in accordance with the new goals.

Change is hard, and it goes better when everyone is on board. In order to ensure that employees change their behaviour and work towards the goals you have defined, you will need to have the data to monitor performance.

You probably have an instinct for which of your field workers are the best performers, but your analysis of performance metrics will give you hard evidence, and also help evaluate why they are the best. You probably also know which workers consistently fail to hit their targets. Analysis will show you what to do to help them improve –and to monitor their progress. Once you know the drivers of excellence, you can replicate them throughout the organisation, working with employees to improve skills and capabilities where needed.

It also helps if employees understand the wider company strategy and how their own performance indicators and goals align. We recommend adopting OKRs, a method used by Google to align organisational strategy with individual goals and improve performance.

OKR stands for Objectives and Key Results — the process by which leaders and their teams set ambitious, measurable goals each quarter — are a critical component of how Google’s leaders managed Google’s growth from day one. By focusing on a few priorities, identifying the metrics that measure progress towards those goals, and quantifying the impact of that progress, OKRs equipped teams at Google with what they needed to think big, get alignment across the organisation, and execute on their ambitious plans.

Once you have decided on the metrics to focus on, you can begin to make changes. These changes can be at any level. They can be to processes or procedures, in which case they will require everyone to know about and follow them.

They can be to documentation, giving people new information, or to the website, to change customer behaviour. They can impact the field service technicians directly, or indirectly - the example below involved a small change to the call centre script, not to engineering processes - but it had a big impact on a key performance metric for engineers.

There are many barriers to implementing change. Even if you have employees on board and the whole company aligned around the strategy, it can be hard to know which changes to prioritise, how they will affect other metrics, how much it will cost to implement the changes, and what will be the return on investment. At this stage, modelling the likely impact is invaluable, as it will help you prioritise.

Step 6 - Observe and Analyse Outcomes

Once improvements have been implemented, the next step is to observe the impact on performance and analyse the outcomes.

As a service leader you need to have full visibility of what is happening in the field in real time, so you and your team can make adjustments and prevent incidents before they arise. Ideally you should be able to see, at a glance, the status of all your key metrics, and be alerted if any are in jeopardy as well as any variations from the plan for the shift. Short interval control is another technique used in lean manufacturing to drive improvements, during each shift; with access to field service data and analytics tools to gain insight in real time, service managers can adopt this approach. This approach is also adapted from agile software development environments which advocate testing and learning with real customers, in real time, using data to assess the impact of each change.

Also, as you make the changes, capture those that are driving improvements, as well as those that are having little direct impact, but may impact further down the line. You might want to pilot in one region, capturing what has worked and what has not. You can then use the region staff as ambassadors of change across the broader organisation.

As well as acting in real time to change outcomes during the shift, you need to be able to analyse the impact of changes over time, so you can see whether improvements have been effective and if you need to dial up changes, dial down, or try something else. You can even conduct controlled experiments by using AB testing - trying two different approaches with different, randomly chosen sets of technicians, or in different regions, to see which improvements work the best.

This is the step where the value of the data driven approach comes into its own.

Taking the outcomes of improvements, and feeding back into the data for analysis at step one creates a feedback loop, enabling you to test and learn, freeing you from having to make gut decisions, and harnessing the power of continuous improvement to get to exceptional field service.

With a continual improvement approach, the £500K or more you could save in productivity isn’t a one-off. You can use that saving to do more, or to reduce headcount in year one, and also expect to see a similar improvement and saving in years two, three and onward. The goalposts are always moving in field service, as technology advances, competitors improve and customer expectations increase, so there will always be improvements you can make, regardless of the quality of your service at this moment.

So now you know the seven steps, what are you waiting for? It’s easy to describe, but not so easy to do.

In reality, getting to exceptional will require you to have the following:

• high quality, accurate, real-time data
• the ability to analyse the data to gain insight, both in real time, and in retrospect
• the experience to decide how to apply the insight
• the foresight to model the impact of changes and the ROI of planned actions
• the insight to know what exceptional looks like, and to set appropriate benchmarks
• the agility to test changes and learn from the outcomes
• the leadership to drive through improvements and manage change throughout the organisation

We know that field service leaders are a talented bunch, but that is still a tall order. Fortunately, there is no pressure to take all seven steps at once. Getting to exceptional is a long-term process and just taking the first step will deliver business benefits. So how do you take that first step? Advances in technology mean that there is support available. Digital transformation means so much more than just digitising paper-based processes, or automating manual processes. We believe that all of the hundreds of decisions that are made every day in field service operations can and should be driven by data and analysis, not by gut instinct, or expediency.

For many companies, the digital transformation challenge has moved on from being able to collect the data, to knowing how to analyse it, and what actions to take. Advances in AI such as machine learning mean that we can start to automate the process of continuous improvement. The goal should be that the system can spot a problem and recommend a fix without human intervention, and then track that change through the organisation and drive adoption in the field. The future of field service belongs to those companies that can adopt advanced analytics, together with smart business approaches, to use data to drive exceptional field service.