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.

 

How Energy Conservation saved Fambeau River Paper

Rising energy costs caught this Wisconsin paper mill napping, and it soon shut down because it was unable to innovate. Someone else bought it and turned it around by measuring, modifying, monitoring and listening to people.

The Fambeau River Paper Mill in Prince County, Wisconsin USA employed 13% of the city?s residents until rising energy costs shut it down in 2006. Critics wrote it off as an energy dinosaur unable to adapt. But that was before another company bought it out and resuscitated it as a fleet-footed winner.

Its collapse was a long time coming and almost inevitable. Wisconsin electricity prices had grown a third since 1997, the machinery was antiquated and the dependence on fossil power absolute. So what did the new owners change, and is there anything we can learn from this?

The key to understanding what suddenly went right was the new owners? ability to listen. They requested a government Energy Assessment that suggested a number of small step changes that took them where they needed to go in terms of energy saving. These included enhancements in steam systems and fuel switch modifications. However they needed more than that.

The second game changer was tracking down key members of the old workforce and listening to them too. This combination enabled them to finally hire back 92% of the original labour force under the same terms and conditions – and still make a profit (the other 8% had moved on elsewhere or retired). The combined energy savings produced a payback plan of 5.25 years. Three years into the project their capital investment of $15 million had already clawed back the following electricity savings.

  • Evaporator Temperature Control $2,245,000
  • Hot Water Heat Recovery $2,105,000
  • Paper Machine Devronisers $1,400,000
  • Increased Boiler Output $1,134,000
  • Paper Machine Modifications; $761,000
  • Motive Air Dryer $610,000
  • Accumulator Savings $448,000
  • Densified Fuels Plant $356,000

In terms of carbon dioxide produced, the Fambeau River Paper Mill?s contribution dropped from 1 ton to 600 pounds.

How well do you know where your company?s energy spend is concentrated, and how this compares with your industry average; could you be doing better if you innovated, and by how much? Get these questions answered by asking ecoVaro how easy it could be to get on top of your carbon metrics. This could cost you a phone call and a payback on it so rapid it’s not worth stopping to calculate.

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Data Leakage Prevention – Protecting Sensitive Information

When DuPont lost $400 million in intellectual property, it wasn’t because a hacker from the other side of the world infiltrated their system. The information was simply stolen by a former employee. Alarmingly, data loss incidents are not always caused by deliberate actions.

A file containing personal information accidentally attached to an email and sent to multiple recipients; financial data stored in a USB pen drive, accidentally left in a restaurant; or bank account data of colleagues, inadvertently posted on a company website – these are also some of the everyday causes of data loss.

A report done by research company Infowatch regarding global data leaks in 2010 showed that there were actually more accidental data leaks in that year compared to intentional ones. Accidental leaks comprised 53%, while intentional leaks comprised 42% (the rest were unidentified).

But even if they ?only? happened accidentally, breach incidents like these can still be very costly. The tens of thousands of dollars that you could sometimes end up paying in civil penalties (as in the case when you lose other people?s personal information) can just be the beginning. More costly than this is the loss of customer and investor confidence. Once you lose those, you could consequently lose a considerable portion of your business.

Confidential information that may already be leaking out right under your nose

With all the data you collect, process, exchange, and store electronically every day, your IT system has surely now become a storehouse of sensitive information. Some of them, you may be even taking for granted.

But imagine what would happen if any of the following trade secrets fell into the wrong hands: marketing plans, confidential customer information, pricing data, product development strategies, business plans, supplier information, source codes, and employee salaries.

These are not the only kind of data that you should be worried about. You could also get into trouble if your sloppy IT security fails to protect employee or client personal information such as their names; social security numbers; drivers license numbers; or bank account numbers and credit/debit card numbers along with their corresponding PINs.

In some countries, you could face onerous data breach notification requirements and heavy fines when these kind of data are involved.

There are now more holes to plug

It’s not just the different varieties of sensitive electronic information that you have to worry about. Because these data can take on different forms, i.e. data-at-rest, data-in-motion, and data-at-the-endpoints, you also need to take aim at different areas in your IT system.

Sensitive information can be found ?at rest? in each of your employees? hard disks, in your servers, storage disks, and in off-site backup disks. They can also be found ?in motion? in email, instant messaging, social networking messaging, P2P file sharing, ftp, http, and so on.

That’s not all. Your highly mobile workforce may have already introduced yet another high-risk area into your system: data-at-the-endpoints. This includes USB flash-disks, laptops, portable hard disks, CDs, and even smartphones.

The main challenge of data leak prevention

Having been made aware of the various aspects of data leakage, have you already come to grips with the extent of the task at hand?

There are two major things you need to do here to prevent data leakage.

One, you need to identify what data you have that can be considered as sensitive/confidential information. Of course you have financial information and employee salaries in your files. But do you also store personally identifiable information? Do you have trade secrets that are stored in electronic form?

Two, you need to pinpoint their locations. Are they only on your hard disks and laptops? Or have they made their way to flash drives, CDs/DVDs, or portable HDDs? Are they being transmitted through email or any other file transfer media?

The reason why you need to know what your sensitive data are as well as where they are is because you would like all efforts of securing them to be as efficient and unobtrusive as possible.

Let’s say, as a way of protecting your data, you decide to implement encryption. Since encryption can consume a lot of storage space and significantly reduce performance, it may be impractical to encrypt your entire database or all your files. For the same reason, you wouldn’t want to encrypt every single email that you send.

Thus, the best way would be to encrypt only the data that really need encryption. But again, you need to know what data needs to be encrypted and where those data can be found. That alone is no simple task.

Not only will you need to deal with the data you already have, you will also have to worry about the data that will go through your systems during the course of your day-to-day transactions.

Identifying sensitive data as it enters or leaves your system, goes through your network, or gets stored in your file system or database, and then applying the necessary security actions should be done automatically and intelligently. Otherwise, you could end up spending on a lot of man-hours or, worse, wasting them on a lot of false positives and negatives.

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