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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How Accenture Keeps Rolling Out Sustainability

Multinational management-consulting and technology-services company Accenture has a good eye for sniffing out new business, with 305,000 employees advancing its interests in more than 200 cities in 56 countries evidence. Last year, it netted US$30 billion profit that is a tidy sum of money in anybody?s books.

Accenture also practices what it preaches. This is maximum business efficiency within moral standards. It tracks its carbon emissions from its offices around the world. Being a technology services company it is unsurprising that it automated the process. Being management consultants it can drill down to finest detail in its search for continuous improvement.

As a forward-thinking company Accenture is committed to transplanting its business skills into other organizations, in order to drive higher performance and sustain greater profits in the long term. It works with clients across borders and industries to integrate sustainability into their business models, and find effective ways to lighten carbon footprints.

The City of Seattle in Washington is a case in point. Following a proud history of nature and energy conservation, it engaged Accenture in 2013 to help it reduce downtown power consumption by 25%. Other project members were Microsoft supplying software, the local power utility for technical advice, and a non-profit to set up a smart building program. The initiative uses cloud services to process the big data generated by a host of building management services, plus a multitude of sensors, controls and meters.

The project is vital for the City. It wants to continue expanding but needs to avoid another power plant polluting its skyline. At the time of writing, the pilot sites had proved successful and the program was rolling out. Seattle?s next challenge is to acquire 15% of its energy from renewable sources by 2020.

The smart building solutions Seattle trialled in five downtown buildings, had a further welcome spinoff; by reducing operating times, facility managers can look forward to extended equipment life and fewer maintenance downtimes. The green building philosophy is alive and well in the City of Seattle, driven both by necessity and vision.

It is a no longer as question of if – but when – other urban communities follow suit. EcoVaro believes it is time long due for individual companies to start enjoying lower energy costs plus the prospect of profitably trading carbon credits. The process begins with measuring what you have and identifying cost-effective savings.

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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 Woes – Burden in SOX Compliance and Other Regulations

End User Computing (EUC) or end User Developed Application (UDA) systems like spreadsheets used to be ideal ad-hoc solutions for data processing and financial reporting. But those days are long gone.

Today, due to regulations like the:

  • Sarbanes-Oxley (SOX) Act,
  • Dodd-Frank Act,
  • IFRS (International Financial Reporting Standards),
  • E.U. Data Protection Directive,
  • Basel II,
  • NAIC Model Audit Rules,
  • FAS 157,
  • yes, there?s more ? and counting

a company can be bogged down when it tries to comply with such regulations while maintaining spreadsheet-reliant financial and information systems.

In an age where regulatory compliance have become part of the norm, companies need to enforce more stringent control measures like version control, access control, testing, reconciliation, and many others, in order to pass audits and to ensure that their spreadsheets are giving them only accurate and reliable information.

Now, the problem is, these control measures aren’t exactly tailor-made for a spreadsheet environment. While yes, it is possible to set up a spreadsheet and EUC control environment that utilises best practices, this is a potentially expensive, laborious, and time-consuming exercise, and even then, the system will still not be as foolproof or efficient as the regulations call for.

Testing and reconciliation alone can cost a significant amount of time and money to be effective:

  1. It requires multiple testers who need to test spreadsheets down to the cell level.
  2. Testers will have to deal with terribly disorganized and complicated spreadsheet systems that typically involve single cells being fed information by other cells in other sheets, which in turn may be found in other workbooks, or in another folder.
  3. Each month, an organisation may have new spreadsheets with new links, new macros, new formulas, new locations, and hence new objects to test.
  4. Spreadsheets rarely come with any kind of supporting documentation and version control, further hampering the verification process.
  5. Because Windows won’t allow you to open two Excel files with the same name simultaneously and because a succession of monthly-revised spreadsheets separated by mere folders but still bearing the same name is common in spreadsheet systems, it would be difficult to compare one spreadsheet with any of its older versions.

But testing and reconciliation are just two of the many activities that make regulatory compliance terribly tedious for a spreadsheet-reliant organisation. Therefore, the sheer intricacy of spreadsheet systems make examining and maintaining them next to impossible.

On the other hand, you can’t afford not to take these regulations seriously. Non-compliance with regulatory mandates can have dire consequences, not the least of which is the loss of investor confidence. And when investors start to doubt the management’s capability, customers will start to walk away too. Now that is a loss your competitors will only be too happy to gain.

Learn more about our server application solutions and discover a better way to comply with regulations.

More Spreadsheet Blogs


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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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