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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8 Best Practices To Reduce Technical Debt

When past actions in software development return to haunt you…

Is your business being bogged down by technical debt? Let’s look at measures that you can take to reduce it and scale your operations without the weight pulling you back. 

 

Work with a flexible architecture.

Right from the word go, you want to use architecture whose design is malleable, especially with the rapid rate of software evolution witnessed today. Going with an architecture that keeps calling for too much refactoring, or whose design won’t accommodate future changes will leave you with costly technical debt. Use scalable architecture that allows you to modify or add new features in future releases. While on this, complex features required in the final product should be discussed at the planning stage, that way simplified solutions that will be easier to implement can be identified, as this will lead to less technical debt in the long run. 

 

The Deal with Refactoring 

This is basically cleaning up the code structure without changing its behaviour. With the updates, patches, and new functionalities that are added to the systems and applications, each change comes with the threat of more technical debt. Additionally, organisations are increasingly moving their IT infrastructure from on-premises facilities to colocation data centres and deploying them on the cloud. In such scenarios, some workarounds are often needed to enable the systems to function in the new environments, which they hadn’t been initially developed to accommodate. Here, you will need to take some time to refactor the existing system regularly, streamlining the code and optimizing its performance – and this will be key to pay down the tech debt. When working with a flexible architecture from the start, the amount of work that goes into this will be reduced, meaning there’ll be less tech debt involved. 

 

Run discovery tests

Discovery testing essentially takes place even before a line of code is written for the system or application. This takes place at the product definition stage, where human insight software is used to understand the needs of the customer and is particularly helpful in setting priorities for the development work that will be carried out. It gives your business the opportunity to minimize the technical debt by allowing customers to give you a roadmap of the most pertinent features desired from the product. 

 

Routine code review

Getting a fresh look at the product or application from different sets of eyes in the development team will improve the quality of the code, thus reducing technical debt. There’s a catch though – this should be planned in a convenient way that doesn’t end up becoming a burden for the developers. Here are suggestions:

Break down pull requests

Instead of having complex pull requests where numerous changes in the code are introduced at a go, have this broken down into smaller manageable pull requests, each with a brief title and description about it. This will be easier for the code reviewer to analyse. 

● Define preferred coding practices

Documenting the preferred coding style will result in cleaner code, meaning the developers will focus their effort on reviewing the code itself, not losing time on code format debates.

 

Test automation

Relying only on scheduled manual testing opens you up to the risk of technical debt accruing rapidly, and not having sufficient resources to deal with the accumulated problems when they are identified. Automated testing on the other hand enables issues to be uncovered quicker, and with more precision. For instance, you can have automated unit tests that look at the functioning of the individual components of a system, or regression testing where the focus is on whether the code changes that have been implemented have affected related components of the system. However, establishing and maintaining automated testing will require quite some effort – making it more feasible for the long-term projects.

 

Keep a repository that tracks changes made

Do you have a record of changes made in the software? Keeping one in a repository that is accessible by the development team will make it easy to pin-point problems at their source. For instance, when software is being migrated to a new environment, or legacy software is in the process of being modernised, you will want to have an accurate record of changes that are being introduced, that way if there is an undesired impact on the system this it will be easier to zero-down on the cause.

 

Bring non-technical stakeholders on board

Does this conversation sound familiar?

Development Team: “We need to refactor the messy code quickly”

Product Team: “We have no idea what you are saying”

On one hand, you have the management or product team defining the product requirements, creating a project roadmap, and setting its milestones. On the other hand, there’s the software development/engineering that’s primarily focused on the product functionality, technical operations and clearing the backlog in code fixes. Poor communication between the two teams is actually a leading cause of technical debt.

For you to take concrete steps in managing your technical debt, the decision-makers in the organisation should understand its significance, and the necessity of reducing it. Explain to them how the debt occurred and why steps need to be taken to pay it down – but you can’t just bombard them with tech phrases and expect them to follow your thought process. 

So how do you go about it? Reframe the issues involved with the technical debt and explain the business value or impact of the code changes. Basically, the development team should approach it from a business point of view, and educate the management or production team about the cost of the technical debt. This can include aspects such as expenses in changing the code, salaries for the software engineers especially when the development team will need to be increased due to the workload piling up, as well as the revenue that is lost when the technical debt is allowed to spiral. 

The goal here is to show the management or production team how issues like failing to properly define the product requirements will slow down future software development, or how rushing the code will affect the next releases. That way, there will be better collaboration between the teams involved in the project. 

 

Allocate time and resources specifically for reducing technical debt

With management understanding that working with low-quality code is just like incurring financial debt and it will slow down product development, insist on setting time to deal with the debt. 

For instance, when it comes to the timing of application releases, meetings can be conducted to review short- and longer-term priorities. These meetings – where the development team and product team or management are brought together, the developers point out the software issues that should be resolved as a priority as they may create more technical debt. Management then ensures that budgets and plans are put in place to explicitly deal with those ongoing maintenance costs.

 

Retire old platforms

While most of the resources are going into developing new applications and improving the systems being used, the organisation should also focus on retiring the old applications, libraries, platforms, and the code modules. It’s recommended that you factor this into the application release plans, complete with the dates, processes and costs for the systems involved. 

 

Total overhaul

When the cost and effort of dealing with the technical debt far outweighs the benefits, then you may have to replace the entire system. At this tipping point, you’re not getting value from the technical debt, and it has become a painful issue that’s causing your organisation lots of difficulties. For instance, you may be dealing with legacy software where fixing it to support future developments has simply become too complicated. The patches available may only resolve specific issues with the system, and still leave you with lots of technical debt. Here, the best way out is to replace the system in its entirety. 

 

Final thoughts

Every software company has some level of tech debt. Just like financial debt, it is useful when properly managed, and a problem when ignored or allowed to spiral out of control. It’s a tradeoff between design/development actions and business goals. By taking measures to pay down your organization’s debt and address its interest as it accrues, you will avoid situations where short term solutions undermine your long-term goals. This is also key to enable your business to transition to using complex IT solutions easier, and even make the migration between data centres much smoother. These 8 measures will enable you to manage your technical debt better to prevent it from being the bottleneck that stifles your growth.

Spreadsheet Reporting – No Room in Your Company in an Age of Business Intelligence

It doesn’t take a genius to understand why spreadsheet reporting still pervades the enterprise despite the rise of a complex but highly effective IT solution known to big shot CIOs as Business Intelligence or BI.

If you’re still in the dark as to what BI is, don’t worry because we?ll enlighten you shortly.

Business decisions from disparate data sources

In the meantime, let’s talk about how you make business decisions. If you’re a top executive, then you make decisions based largely on reports submitted to you by your managers, department heads, and so on. They in turn obtain information from different sources, like the company ERP and CRM as well as other external sources (e.g. market surveys).

Now, before their reports ever reach your desk, a lot of data is extracted, shared, filtered, analysed, consolidated, and summarised so that they become actionable information. In all these activities, one software tool gets to take part in most of the action – the spreadsheet.

The problem with spreadsheet reporting

The problem with spreadsheets is that they have very poor built-in controls. Thus, they are susceptible to human errors and are vulnerable to fraud. What’s more, collecting data and manually consolidating them into spreadsheets can be very laborious and time consuming.

If you don’t get accurate, reliable information, your judgement will be fuzzy and your business decisions compromised. In addition, if you don’t receive the information you need on time, your business will constantly be at risk of breaching critical thresholds, which may even force it to spin out of control.

Business Intelligence – actionable information on time

This is mainly the reason why large companies implement Business Intelligence systems. BI systems are equipped with built-in features like reports, dashboards, and alerts.

Reports consolidate data and present them in a consistent format composed of intuitive text, graphs, and charts. The main purpose of having a consistent format is so that you will know what kind of information to expect and how the information is arranged. That way, you don’t waste time searching or making heads or tails out of the data in front of you.

Dashboards, on the other hand, present information through visual representations composed of graphs and gauges that are aimed at tracking your business metrics and goals. The main function of dashboards is to feed you with actionable information at a glance.

Finally, alerts keep you informed when certain conditions are met or critical thresholds are breached. Because their main purpose is to prompt you at the soonest possible time wherever you are, a typical alert can come in the form of an SMS message or an email.

As you can see, all three features are designed to get you making well-informed decisions as quickly as possible.

The problem with Business Intelligence and the alternative solution

The usual problem with full BI systems is that they can be very costly. Hence, if your organisation does end up implementing one, chances are, not everyone under you will be able to access it. As a result, some departments will be forced to go back to using spreadsheets.

If your company cannot afford a full BI system, then that probably means you don’t need one. What you need is a more affordable alternative. There are actually Software as a Service (SaaS) Business Intelligence solutions that may not be as comprehensive as a full BI system, but which may suffice for small and mid-sized businesses.

The disadvantages of spreadsheets are more damaging than you could have ever expected. Be free of it now.

 

More Spreadsheet Blogs

 

Spreadsheet Risks in Banks

 

Top 10 Disadvantages of Spreadsheets

 

Disadvantages of Spreadsheets – obstacles to compliance in the Healthcare Industry

 

How Internal Auditors can win the War against Spreadsheet Fraud

 

Spreadsheet Reporting – No Room in your company in an age of Business Intelligence

 

Still looking for a Way to Consolidate Excel Spreadsheets?

 

Disadvantages of Spreadsheets

 

Spreadsheet woes – ill equipped for an Agile Business Environment

 

Spreadsheet Fraud

 

Spreadsheet Woes – Limited features for easy adoption of a control framework

 

Spreadsheet woes – Burden in SOX Compliance and other Regulations

 

Spreadsheet Risk Issues

 

Server Application Solutions – Don’t let Spreadsheets hold your Business back

 

Why Spreadsheets can send the pillars of Solvency II crashing down

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Is Your Project Agile, a Scrum or a Kanban?

Few projects pan out the way we expect when starting out. This is normal in any creative planning phase. We half suspect the ones that follow a straight line are the exceptions to the rule. Urban legend has it; Edison made a thousand prototypes before his first bulb lit up, and then went on to comment, ?genius is 1% inspiration, 99% perspiration?. Later, he added that many of life’s failures are people who did not realise just how close they were to success when they gave up.

So be it to this day, and so be it with project planning too. There is no one size fits all approach when it comes to it. Agile, Scrum and Kanban each have their supporters and places where they do well. Project planning often works best when we use a sequential combination of them, appropriate to what is currently happening on the ground.

Of the three, Agile is by far the most comprehensive. It provides a structure that begins with project vision / conceptualisation, and goes as far as celebration when the job is over, and retrospective discussion afterwards. However, the emphasis on daily planning meetings may dent freethinking, and even smother it.

Scrum on the other hand says ?forget all that bureaucracy?. There is a job to do and today is the day we are going to do it. Although the core Agile teamwork is still there it ignores macro project planning, and could not be bothered with staying in touch with customers. If using Scrum, it is best to give those jobs to someone else.

The joker in the pack is Kanban, It believes that rules are there to substitute for thought, and that true progress only comes from responsible freedom. It belongs in mature organisations that have passed through Scrum and Agile phases and have embarked on a voyage towards perfection.

That said, there can be no substitute for human leadership, especially when defined as the social influence that binds the efforts of others towards a single task.

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