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

?

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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Authentication and Access Control

Threats to your data can come from external or internal sources.

  1. There are individuals who don’t have the authorisation but are driven by malicious intentions to gain access to certain information. This may refer to individuals who already belong to your organisation (but don’t have the necessary access rights) as well as those who don’t.
  2. There are individuals who have both the authorisation and, unfortunately, the malicious intentions over certain information.
  3. Finally, there are individuals who have the authorisation, no malicious intentions, but have accidentally exposed the information in question to those without the proper authority.

While curbing threats 2 and 3 would require other methods, threat #1 can be countered if the right authentication and access control systems are in place.

Here’s what we can do for you:

  • Work with your key personnel to determine who gets access to what.
  • Help you decide whether a single factor or a two-factor authentication (2FA) is appropriate for your organisation and recommend which factors are most suitable. Login methods may include but are not limited to the following:
    • biometric devices
    • Kerberos tickets
    • mobile phones
    • passwords
    • PKI certificates
    • proximity cards
    • smart cards
    • tokens
  • Install the necessary infrastructure needed for the factors chosen. For instance, if you opt to use biometrics, then biometric scanners will be installed. We’ll make sure that the authentication terminals are situated in places where achieving optimal traffic and work flow has been taken into consideration.

Other defences we’re capable of putting up include:

New Focus on Monitoring Soil

There is nothing new about monitoring soil in arid conditions. South Africa and Israel have been doing it for decades. However climate change has increased its urgency as the world comes to terms with pressure on the food chain. Denizon decided to explore trends at the macro first world level and the micro third world one.

In America, the Coordinated National Soil Moisture Network is going ahead with plans to create a database of federal and state monitoring networks and numerical modelling techniques, with an eye on soil-moisture database integration. This is a component of the National Drought Resilience Partnership that slots into Barrack Obama?s Climate Action Plan.

This far-reaching program reaches into every corner of American life to address the twin scourges of droughts and inundation, and the agency director has called it ?probably ?… one of the most innovative inter-agency tools on the planet?. The pilot project involving remote moisture sensing and satellite observation targets Oklahoma, North Texas and surrounding areas.

Africa has similar needs but lacks America?s financial muscle. Princeton University ecohydrologist Kelly Caylor is bridging the gap in Kenya and Zambia by using cell phone technology to transmit ecodata collected by low-cost ?pulsepods?.

He deploys the pods about the size of smoke alarms to measure plants and their environment.?Aspects include soil moisture to estimate how much water they are using, and sunlight to approximate the rate of photosynthesis. Each pod holds seven to eight sensors, can operate on or above the ground, and transmits the data via sms.

While the system is working well at academic level, there is more to do before the information is useful to subsistence rural farmers living from hand to mouth. The raw data stream requires interpretation and the analysis must come through trusted channels most likely to be the government and tribal chiefs. Kelly Caylor cites the example of a sick child. The temperature reading has no use until a trusted source interprets it.

He has a vision of climate-smart agriculture where tradition gives way to global warming. He involves local farmers in his research by enrolling them when he places pods, and asking them to sms weekly weather reports to him that he correlates with the sensor data. As trust builds, he hopes to help them choose more climate-friendly crops and learn how to reallocate labour as seasons change.

Using Pull Systems to Optimise Work Flows in Call Centres

When call centres emerged towards the end of the 20th century, they deserved their name ?the sweatshops of the nineties?. A new brand of low-paid workers crammed into tiny cubicles to interact with consumers who were still trying to understand the system. Supervisors followed ?scientific management? principles aimed at maximising call-agent activity. When there was sudden surge in incoming calls, systems and customer care fell over.

The flow is nowadays in the opposite direction. Systems borrowed from manufacturing like Kanban, Pull, and Levelling are in place enabling a more customer-oriented approach. In this short article, our focus is on Pull Systems. We discuss what are they, and how they can make modern call centres even better for both sets of stakeholders.

Pull Systems from a Manufacturing Perspective

Manufacturing has traditionally been push-based. Sums are done, demand predicted, raw materials ordered and the machines turned on. Manufacturers send out representatives to obtain orders and push out stock. If the sums turn out wrong inventories rise, and stock holding costs increase. The consumer is on the receiving end again and the accountant is irritable all day long.

Just-in-time thinking has evolved a pull-based approach to manufacturing. This limits inventories to anticipated demand in the time it takes to manufacture more, plus a cushion as a trigger. When the cushion is gone, demand-pull spurs the factory into action. This approach brings us closer to only making what we can sell. The consumer benefits from a lower price and the accountant smiles again.

Are Pull Systems Possible in Dual Call Centres

There are many comments in the public domain regarding the practicality of using lean pull systems to regulate call centre workflow. Critics point to the practical impossibility of limiting the number of incoming callers. They believe a call centre must answer all inbound calls within a target period, or lose its clients to the competition.

In this world-view customers are often the losers. At peak times, operators can seem keen to shrug them off with canned answers. When things are quiet, they languidly explain things to keep their occupancy levels high. But this is not the end of the discussion, because modern call centres do more than just take inbound calls.

Using the Pull System Approach in Dual Call Centres

Most call centre support-desks originally focused are handling technical queries on behalf of a number of clients. When these clients? customers called in, their staff used operator?s guides to help them answer specific queries. Financial models?determined staffing levels and the number of ?man-hours? available daily. Using a manufacturing analogy, they used a push-approach to decide the amount of effort they were going to put out, and that is where they planted their standard.

Since these early 1990 days, advanced telephony on the internet has empowered call centres to provide additional remote services in any country with these networks. They have added sales and marketing to their business models, and increased their revenue through commissions. They have control over activity levels in this part of their business. They have the power to decide how many calls they are going to make, and within reason when they are going to make them.

This dichotomy of being passive regarding incoming traffic on the one hand, and having active control over outgoing calls on the other, opens up the possibility of a partly pull-based lean approach to call centre operation. In this model, a switching mechanism moves dual trained operators between call centre duties and marketing activities, as required by the volume of call centre traffic, thus making a pull system viable in dual call centres.

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