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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What Is Technical Debt? A Complete Guide

You buy the latest iPhone on credit. Turn to fast car loan services to get yourself those wheels you’ve been eyeing for a while. Take out a mortgage to realise your dream of being a homeowner. Regardless of the motive, the common denominator is going into financial debt to achieve something today, and pay it off in future, with interest. The final cost will be higher than the loan value that you took out in the first place. However, debt is not limited to the financial world.

Technical Debt Definition

Technical debt – which is also referred to as code debt, design debt or tech debt – is the result of the development team taking shortcuts in the code to release a product today, which will need to be fixed later on. The quality of the code takes a backseat to issues like market forces, such as when there’s pressure to get a product out there to beat a deadline, front-run the competition, or even calm jittery consumers. Creating perfect code would take time, so the team opts for a compromised version, which they will come back later to resolve. It’s basically using a speedy temporary fix instead of waiting for a more comprehensive solution whose development would be slower.

How rampant is it? 25% of the development time in large software organisations is actually spent dealing with tech debt, according to a multiple case study of 15 organizations. “Large” here means organizations with over 250 employees. It is estimated that global technical debt will cost companies $4 trillion by 2024.

Is there interest on technical debt?

When you take out a mortgage or service a car loan, the longer that it takes to clear it the higher the interest will be. A similar case applies to technical debt. In the rush to release the software, it comes with problems like bugs in the code, incompatibility with some applications that would need it, absent documentation, and other issues that pop up over time. This will affect the usability of the product, slow down operations – and even grind systems to a halt, costing your business. Here’s the catch: just like the financial loan, the longer that one takes before resolving the issues with rushed software, the greater the problems will pile up, and more it will take to rectify and implement changes. This additional rework that will be required in future is the interest on the technical debt.

Reasons For Getting Into Technical Debt

In the financial world, there are good and bad reasons for getting into debt. Taking a loan to boost your business cashflow or buy that piece of land where you will build your home – these are understandable. Buying an expensive umbrella on credit because ‘it will go with your outfit‘ won’t win you an award for prudent financial management. This also applies to technical debt.

There are situations where product delivery takes precedence over having completely clean code, such as for start-ups that need their operations to keep running for the brand to remain relevant, a fintech app that consumers rely on daily, or situations where user feedback is needed for modifications to be made to the software early. On the other hand, incurring technical debt because the design team chooses to focus on other products that are more interesting, thus neglecting the software and only releasing a “just-usable” version will be a bad reason.

Some of the common reasons for technical debt include:

  • Inadequate project definition at the start – Where failing to accurately define product requirements up-front leads to software development that will need to be reworked later
  • Business pressure – Here the business is under pressure to release a product, such as an app or upgrade quickly before the required changes to the code are completed.
  • Lacking a test suite – Without the environment to exhaustively check for bugs and apply fixes before the public release of a product, more resources will be required later to resolve them as they arise.
  • Poor collaboration – From inadequate communication amongst the different product development teams and across the business hierarchy, to junior developers not being mentored properly, these will contribute to technical debt with the products that are released.
  • Lack of documentation – Have you launched code without its supporting documentation? This is a debt that will need to be fulfilled.
  • Parallel development – This is seen when working on different sections of a product in isolation which will, later on, need to be merged into a single source. The greater the extent of modification on an individual branch – especially when it affects its compatibility with the rest of the code, the higher the technical debt.
  • Skipping industrial standards – If you fail to adhere to industry-standard features and technologies when developing the product, there will be technical debt because you will eventually need to rework the product to align with them for it to continue being relevant.
  • Last-minute product changes – Incorporating changes that hadn’t been planned for just before its release will affect the future development of the product due to the checks, documentation and modifications that will be required later on

Types of Technical Debt

There are various types of technical debt, and this will largely depend on how you look at it.

  • Intentional technical debt – which is the debt that is consciously taken on as a strategy in the business operations.
  • Unintentional technical debt – where the debt is non-strategic, usually the consequences of a poor job being done.

This is further expounded in the Technical Debt Quadrant” put forth by Martin Fowler, which attempts to categorise it based on the context and intent:

Technical Debt Quadrant

Source: MartinFowler.com

Final thoughts

Technical debt is common, and not inherently bad. Just like financial debt, it will depend on the purpose that it has been taken up, and plans to clear it. Start-ups battling with pressure to launch their products and get ahead, software companies that have cut-throat competition to deliver fast – development teams usually find themselves having to take on technical debt instead of waiting to launch the products later. In fact, nearly all of the software products in use today have some sort of technical debt.

But no one likes being in debt. Actually, technical staff often find themselves clashing with business executives as they try to emphasise the implications involved when pushing for product launch before the code is completely ready. From a business perspective, it’s all about weighing the trade-offs, when factoring in aspects such as the aspects market situation, competition and consumer needs. So, is technical debt good or bad? It will depend on the context. Look at it this way: just like financial debt, it is not a problem as long as it is manageable. When you exceed your limits and allow the debt to spiral out of control, it can grind your operations to a halt, with the ripple effects cascading through your business.

 

Without Desktop Virtualisation, you can’t attain True Business Continuity

Even if you’ve invested on virtualisation, off-site backup, redundancy, data replication, and other related technologies, I?m willing to bet your BC/DR program still lacks an important ingredient. I bet you’ve forgotten about your end users and their desktops.

Picture this. A major disaster strikes your city and brings your entire main site down. No problem. You’ve got all your data backed up on another site. You just need to connect to it and voila! you’ll be back up and running in no time.

Really?

Do you have PCs ready for your employees to use? Do those machines already have the necessary applications for working on your data? If you still have to install them, then that’s going to take a lot of precious time. When your users get a hold of those machines, will they be facing exactly the same interface that they’ve been used to?

If not, more time will be wasted as they try to familiarise themselves. By the time you’re able to declare ?business as usual?, you’ll have lost customer confidence (or even customers themselves), missed business opportunities, and dropped potential earnings.

That’s not going to happen with desktop virtualisation.

The beauty of?virtualisation

Virtualisation in general is a vital component in modern Business Continuity/Disaster Recovery strategies. For instance, by creating multiple copies of virtualised disks and implementing disk redundancy, your operations can continue even if a disk breaks down. Better yet, if you put copies on separate physical servers, then you can likewise continue even if a physical server breaks down.

You can take an even greater step by placing copies of those disks on an entirely separate geographical location so that if a disaster brings your entire main site down, you can still gain access to your data from the other site.

Because you’re essentially just dealing with files and not physical hardware, virtualisation makes the implementation of redundancy less costly, less tedious, greener, and more effective.

But virtualisation, when used for BC/DR, is mostly focused on the server side. As we’ve pointed out earlier in the article, server side BC/DR efforts are not enough. A significant share of business operations are also dependent on the client side.

Desktop virtualisation (DV) is very similar to server virtualisation. It comes with nearly the same kind of benefits too. That means, a virtualised desktop can be copied just like ordinary files. If you have a copy of a desktop, then you can easily use that if the active copy is destroyed.

In fact, if the PC on which the desktop is running becomes incapacitated, you can simply move to another machine, stream or install a copy of the virtualised desktop there, and get back into the action right away. If all your PCs are incapacitated after a disaster, rapid provisioning of your desktops will keep customers and stakeholders from waiting.

In addition to that, DV will enable your user interface to look like the one you had on your previous PC. This particular feature is actually very important to end users. You see, users normally have their own way of organising things on their desktops. The moment you put them in front of a desktop not their own, even if it has the same OS and the same set of applications, they?ll feel disoriented and won’t be able to perform optimally.

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What GDPR Means in Practice for Irish Business

The General Data Protection Regulation (GDPR) is a European directive aimed at ring-fencing consumer data against illegal or unnecessary access. There is nothing to discuss or debate with local politicians, or the Irish Data Protection Commissioner for that matter. As a European directive, it has over-riding power. To obtain an English version, please visit this link, and select ?EN? from the table of languages.

As you reach for your tea, coffee or Guinness after sighting it, you will be glad to know the Irish Data Protection Commissioner has the lead in turning this into business English we understand. The following diagram should assist you to obtain a quick overview of the process we all have to go through. In this article, we briefly describe what is inside Boxes 1 to 12. The regulation comes into force on 25 May 2018 so we have less than a year to get ready.

The 12 Essential Steps to Implementing the General Data Protection Act

1. Create awareness among your people of what is coming their way. The GDPR has given our regulator discretion to dish out fines up to ?20,000,000 (or 4% of total annual global turnover, whichever is greater) so there is determination to make this happen.

2. Become accountable by understanding the consumer data you hold. Why are you retaining it, how did you obtain it, and why did you originally collect it. Now you know it is there, how much longer will you still need it? How secure is it in your hands, have you ever shared it?

3. Open a communication channel with your staff, your customers, and anyone else using the data. Share how you feel about how accountable you have been with the information in the past. Explain how you plan to comply with the GDPR in future, and what needs to change.

4. Understand the personal privacy entitlement of the subjects of the information. They have rights to access it, correct mistakes, remove information, restrict its use, decline direct marketing, and copy it to their own files. What needs to change in your systems to assure these rights?

5. Issue a policy for allowing consumers access to their information you hold. You must process requests within a month, and you may not charge for the service unless your cost is excessive. You may decline unfounded or excessive demands within your policy guidelines.

6. Adapt to the requirement that you must have a legal basis for everything you do with, and to consumer data. You need to be in a position to justify your actions to the Irish Data Protection Commissioner in the event of a complaint. Having a legitimate interest is no longer sufficient.

7. Ensure that consumer consent to collect, use, and distribute their data is ?freely given, specific, informed, and unambiguous.? From 25 May 2018 onward, this consent will be your only ground to do so. You cannot force consent. Your benchmark becomes what the GDPR says.

8. Issue rules for managing data of underage subjects. This is currently under review and we are awaiting results. Put systems in place to verify age. Set triggers for where guardians must give consent. Make sure age is verifiable. Use language young people understand.

9. Introduce a culture of openness and honesty, whereby breaches of the GDPR are detected, reported, investigated, and resolved. You will have a duty to file a GDPR report with the Data Protection Commissioner within 72 hours, thus it is important to fast track the process.

10. Introduce a policy of conducting a privacy assessment before taking new initiatives. The GDPR calls for ?privacy by deign?, and we need to engineer it in. This may be the right time to appoint a data controller in your company, and start implementing the GDPR while you have time.

11. You may also need to appoint a data protection officer depending on the size of your business. Alternatively, you need to add managing data protection compliance to an employee?s duties, or appoint an external data-protection compliance consultant.

12. Finally, and you will be glad to know this is the end of the list, the GDPR has an international flavour in that multinational organisations will report into the EU Lead Supervisory Authority. This will manage the process centrally while consulting national data authorities.

The GDPR is a project we all need to complete. If we are out of line, it is in our interests to get things straightened out. Once everything is in place, the task should not be too onerous. Getting there could be the pain.

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