How AI Helps Improve Field Service

Its seems that with the current rate of technological innovation that these is something new every single day.  Therefore, you’re always looking forward to a new technological innovation that’s going to help you make your business operations more efficient and automated.

One of the most fascinating milestones in the field of technology is the integration of Artificial Intelligence (AI) in business. In one way or the other, AI gives a glimpse of machine supremacy that allows computers to perform tasks that were initially performed by humans. 

Are machines going to completely replace people in the workplace?

Of course, not.  Technologies like AI and Machine Learning are designed and meant to support employees in doing their tasks too boost their productivity.

AI is predominantly used to eliminate jobs and tasks that humans find boring, demotivating or monotonous. In some cases AI is also used to do jobs that are considered dangerous for humans to preform.

Previously the most common implementations for AI were all about gaming, entertainment, and advanced science,  now it’s spreading into a number of industries including the field service industry.

FieldElite – Field Service Software , can help you optimise the day-to-day operations of your business.

AI in field service management will enhance you business capabilities with:

  • Information Sharing
  • Real Time Updates
  • Automated Workflows
  • Digital Form Data Collection
  • Data Analysis

Improved Customer Service

For Service Based companies, customer retention is vital. Primarily because It can be 5-25 times more costly to acquire a new customer than it is to retain an existing ones.

Therefore customer retention should be a primary focus.? The good news is that by making use of AI you can implement services It can be 5-25 times more costly to acquire a new customer than it is to retain an existing one.

Staying on top of and ensuring you satisfactorily address and meet you customer demands and expectations can be a daunting task.? It can also be an expensive one,? especially for small field service based businesses like :

  • Heating & Plumbing Engineers
  • Electrical Contractors
  • Fire Safety Inspectors
  • HVAC Engineers
  • Facility Management
  • Building, Construction & Trade

Implementing Artificial Intelligence and Machine Learning to automate mundane and repetitive customer administration tasks will enable your staff to be free to provide additional value added tasks for your customers. Making your customers happier.

?Think about the active Chatbots. You can always get complaints directly from customers and address them right away.??

If at any point the customer is unhappy with your services, they can always raise the issue via the Chatbots. Since the bots contain necessary customer information, you can always get back to them and fix the issue at hand.?

With AI in field service, you can solve problems before they arise, or what is otherwise known as predictive maintenance,? In that way, you’ll have better customer relations because you’ll be able to address your customer concerns before they even become aware of them.

Improved Productivity

Scheduling tasks and managing the workforce isn’t a walk in the park. It goes beyond assigning tasks to your team members in the field and giving them deadlines to meet. Whether it’s a small firm or a big organisation, it’s quite difficult to organise the workforce.?

However, adopting Artificial Intelligence can iron out the difficulties most field organisations face in scheduling and managing tasks. Some years back, most firms relied on human intelligence to dispatch jobs to the right people based on given conditions. This was quite difficult, especially that it wasn’t always successful. But thanks to AI. With field service apps like FieldElite scheduling tasks and managing workforce is only a few clicks away.?

What’s more? There?s no room for error. Therefore, you’ll always match the right people for the job. Again, your team will always get tasks on time. That means, the job completion rate will go up, and hence the workforce becomes more productive.?

Predictive Maintenance

Usually, most business operations are based on ?solve the problem as it occurs?, which is just OK. However, it’s not always safe to wait until a problem occurs so that you solve it. Prevention is better than cure, and that’s why Artificial Intelligence comes handy in Field Service.

Using FieldElite Workforce Management Software , you don’t have to wait until something breaks.? Utilizing AI in field service enables you to proactively address field service needs and prevent unforeseen failures and interruptions.?

The ability to predict field service needs through field service apps like FieldElite enables you to make more accurate forecasts. In this way, resource planning is made easier, and as such, you’ll have smoothly running workflows. Again, by taking care of unforeseen circumstances in advance, you’re flexible enough to take care of the unexpected. And that means the overall productivity of your business will go up.

Job Management

Most field service jobs involve multiple stages that can take several days to complete. In addition to this, more often than not, you have to coordinate lots of equipment and contractors at the same time. All these can’t be achieved solely by human efforts. For more successful outcomes, it’s important to incorporate Artificial Intelligence in your field service operations.?

FieldElite is the field service solution that can help you manage sophisticated tasks. The app is packed with field service management tools that enable you to assign complicated tasks and keep track of your field techs. For long-cycle jobs, FieldElite app enables you to follow up on the activities going on the field to ensure they’re completed.?

With AI, there?s no room for error even when the jobs become more sophisticated.

Data Analysis

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Field service industry involves lots of data. Some years back, organisations depended on human intelligence to analyse big data. Well, things still worked out, but as a human is to err, the outcome wasn’t always perfect. However, with Artificial Intelligence data analysis, 100% accuracy in data analysis is achievable. Field service solutions like FieldElite provide sophisticated data analytic tools that enable you to crack massive data and offer accurate solutions.?

FieldElite data analytics capabilities give you an insight into what’s not working and what needs to be improved. In that way, you can always address matters arising and take care of the loopholes.?

It’s time to go paperless with field management software like FieldElite if you?d like to make your business more profitable. Apart from improving the productivity of your workforce, incorporating AI in your business increases profitability. If you’re still doing your usual field rounds with a clipboard, it’s time to simplify your task with FieldElite app.?

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How Bouygues manages an Empire-Sized Footprint

Bouygues is into telecoms / media, and building and road construction. It also knows it has to watch its energy footprint closely. Owning 47% of energy giant Alstom keeps it constantly in the media spotlight. Shall we find out more about its facility management policies?

The journal Premises and Facilities Management interviewed MD Martin Bouygues on his personal opinions concerning managing energy consumption in facilities. He began by commenting that this was hardly a subject for the C-Suite in years gone by. Low-level clerks simply paid the bills following which the actual amounts were lost in the general expenses account. That of course has changed.

Early pressure came from soaring energy bills, which were pursued by a whole host of electricity-saving gadgets. However, it was only after the carbon crisis caught business by surprise that the link was forged to aerial pollution, and the social responsibilities of big business to help with the solution. The duty to have an energy strategy became an obligation eagerly policed by organisations such as Greenpeace.

Unsurprisingly, Martin Bouygues? advice begins with keeping energy consumption and its carbon footprint as high up on the agenda as health and safety. ?It needs bravery and a lot of hard work to get it there,? he says, ?so perseverance is the key?. 

The company has developed proprietary software that enables it to pull data from remote sensors in more than 80 countries every fifteen minutes. A single large building can contribute 50 million data items annually making data big business in the system. Every building has an allocated energy performance contract against which results are reported monthly, as a basis for reviewing progress.

The system is intelligent and able to incorporate low-occupancy periods such as weekends and public holidays. What is measured gets managed. We all know that, but how many of us apply the principle to our energy bills. With assistance from ecoVaro, the possible becomes real.

We offer a similar service to the Bouygues model with one notable exception. You don’t buy the software and you only pay when you use it. Our systems are simply designed for busy financial managers.

Transformation to a process based organisation

Today’s global marketplace rewards nimble organisations that learn and reinvent themselves faster than their competition. Employees at all levels of these organisations see themselves as members of teams responsible for specific business processes, with performance measures tied to the success of the enterprise. As team members, they are “owners” of the process (or processes) to which they are assigned. They are responsible for both the day to day functioning of their process(s), and also for continuously seeking sustainable process improvements.

Transforming a traditionally designed “top down control” enterprise to a process-based organisation built around empowered teams actively engaged in business process re-engineering (BPR) has proven more difficult than many corporate leaders have expected. Poorly planned transformation efforts have resulted in both serious impacts to the bottom line, and even more serious damage to the organisation’s fabric of trust and confidence in leadership.

Tomislav Hernaus, in a publication titled “Generic Process Transformation Model: Transition to Process-based Organisation” has presented an overview of existing approaches to organisational transformation. From the sources reviewed, Heraus has synthesised a set of steps that collectively represent a framework for planning a successful organisational change effort. Key elements identified by Hernaus include:

Strategic Analysis:

The essential first step in any transformation effort must be development of a clear and practical vision of a future organisation that will be able to profitably compete under anticipated market conditions. That vision must be expected to flex and adjust as understanding of future market conditions change, but it must always be stated in terms that all organisational members can understand.

Identifying Core Business Processes:

With the strategic vision for the organisation in mind, the next step is to define the core business processes necessary for the future organisation to function. These processes may exist across the legacy organisation’s organisational structures.

Designing around Core Processes:

The next step is development of a schematic representation of the “end state” company, organised around the Core Business Processes defined in the previous step.

Transitional Organisational Forms/ Developing Support Systems:

In his transformation model, Hernaus recognises that information management systems designed for the legacy organisation may not be able to meet the needs of the process management teams in the new organisation. Interim management structures (that can function with currently available IT system outputs) may be required to allow IT professionals time to redesign the organisation’s information management system to be flexible enough to meet changing team needs.

Creating Awareness, Understanding, and Acceptance of the Process-based Organisation:

Starting immediately after the completion of the Strategic Analysis process described above, management must devote sufficient resources to assure that all organisation members, especially key managers, have a full understanding of how a process-based organisation functions. In addition, data based process management skills need to be provided to future process team members. It is not enough to schedule communication and training activities, and check them off the list as they are completed. It is critical that management set behavioural criteria for communication and training efforts that allow objective evaluation of the results of these efforts. Management must commit to continuing essential communication and training efforts until success criteria are achieved. During this effort, it may be determined that some members of the organisation are unlikely to ever accept the new roles they will be required to assume in a process-based organization. Replacement of these individuals should be seen as both an organisational necessity and a kindness to the employees affected.

Implementation of Process Teams:

After the completion of required training AND the completion of required IT system changes, process teams can be formally rolled out in a planned sequence. Providing new teams with part time support by qualified facilitators during the firsts weeks after start-up can pay valuable long term dividends.

Team Skill Development and Continuous Process Improvement:

Providing resources for on-going skill development and for providing timely and meaningful recognition of process team successes are two keys for success in a process-based organisation. Qualified individuals with responsibility for providing training and recognition must be clearly identified and provided with sufficient budgetary resources.

The Hernaus model for transformation to a process based organisation is both well thought out and clear. His paper provides an ample resource of references for further study.

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Directions Hadoop is Moving In

Hadoop is a data system so big it is like a virtual jumbo where your PC is a flea. One of the developers named it after his kid?s toy elephant so there is no complicated acronym to stumble over. The system is actually conceptually simple. It has loads of storage capacity and an unusual way of processing data. It does not wait for big files to report in to its software. Instead, it takes the processing system to the data.

The next question is what to do with Hadoop. Perhaps the question would be better expressed as, what can we do with a wonderful opportunity that we could not do before. Certainly, Hadoop is not for storing videos when your laptop starts complaining. The interfaces are clumsy and Hadoop belongs in the realm of large organisations that have the money. Here are two examples to illustrate the point.

Hadoop in Healthcare

In the U.S., healthcare generates more than 150 gigabytes of data annually. Within this data there are important clues that online training provider DeZyre believes could lead to these solutions:

  • Personalised cancer treatments that relate to how individual genomes cause the disease to mutate uniquely
  • Intelligent online analysis of life signs (blood pressure, heart beat, breathing) in remote children?s hospitals treating multiple victims of catastrophes
  • Mining of patient information from health records, financial status and payroll data to understand how these variables impact on patient health
  • Understanding trends in healthcare claims to empower hospitals and health insurers to increase their competitive advantages.
  • New ways to prevent health insurance fraud by correlating it with claims histories, attorney costs and call centre notes.

Hadoop in Retail

The retail industry also generates a vast amount of data, due to consumer volumes and multiple touch points in the delivery funnel. Skillspeed business trainers report the following emerging trends:

  • Tracing individual consumers along the marketing trail to determine individual patterns for different demographics and understand consumers better.
  • Obtaining access to aggregated consumer feedback regarding advertising campaigns, product launches, competitor tactics and so on.
  • Staying with individual consumers as they move through retail outlets and personalising their experience by delivering contextual messages.
  • Understanding the routes that virtual shoppers follow, and adding handy popups with useful hints and tips to encourage them on.
  • Detecting trends in consumer preferences in order to forecast next season sales and stock up or down accordingly.

Where to From Here?

Big data mining is akin to deep space research in that we are exploring fresh frontiers and discovering new worlds of information. The future is as broad as our imagination.?

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