Failure Mode and Effects Analysis

 

Any business in the manufacturing industry would know that anything can happen in the development stages of the product. And while you can certainly learn from each of these failures and improve the process the next time around, doing so would entail a lot of time and money.
A widely-used procedure in operations management utilised to identify and analyse potential reliability problems while still in the early stages of production is the Failure Mode and Effects Analysis (FMEA).

FMEAs help us focus on and understand the impact of possible process or product risks.

The FMEA method for quality is based largely on the traditional practice of achieving product reliability through comprehensive testing and using techniques such as probabilistic reliability modelling. To give us a better understanding of the process, let’s break it down to its two basic components ? the failure mode and the effects analysis.

Failure mode is defined as the means by which something may fail. It essentially answers the question “What could go wrong?” Failure modes are the potential flaws in a process or product that could have an impact on the end user – the customer.

Effects analysis, on the other hand, is the process by which the consequences of these failures are studied.

With the two aspects taken together, the FMEA can help:

  • Discover the possible risks that can come with a product or process;
  • Plan out courses of action to counter these risks, particularly, those with the highest potential impact; and
  • Monitor the action plan results, with emphasis on how risk was reduced.

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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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Transformation to a process based organisation

Today’s global marketplace rewards nimble organisations that learn and reinvent themselves faster than their competition. Employees at all levels of these organisations see themselves as members of teams responsible for specific business processes, with performance measures tied to the success of the enterprise. As team members, they are “owners” of the process (or processes) to which they are assigned. They are responsible for both the day to day functioning of their process(s), and also for continuously seeking sustainable process improvements.

Transforming a traditionally designed “top down control” enterprise to a process-based organisation built around empowered teams actively engaged in business process re-engineering (BPR) has proven more difficult than many corporate leaders have expected. Poorly planned transformation efforts have resulted in both serious impacts to the bottom line, and even more serious damage to the organisation’s fabric of trust and confidence in leadership.

Tomislav Hernaus, in a publication titled “Generic Process Transformation Model: Transition to Process-based Organisation” has presented an overview of existing approaches to organisational transformation. From the sources reviewed, Heraus has synthesised a set of steps that collectively represent a framework for planning a successful organisational change effort. Key elements identified by Hernaus include:

Strategic Analysis:

The essential first step in any transformation effort must be development of a clear and practical vision of a future organisation that will be able to profitably compete under anticipated market conditions. That vision must be expected to flex and adjust as understanding of future market conditions change, but it must always be stated in terms that all organisational members can understand.

Identifying Core Business Processes:

With the strategic vision for the organisation in mind, the next step is to define the core business processes necessary for the future organisation to function. These processes may exist across the legacy organisation’s organisational structures.

Designing around Core Processes:

The next step is development of a schematic representation of the “end state” company, organised around the Core Business Processes defined in the previous step.

Transitional Organisational Forms/ Developing Support Systems:

In his transformation model, Hernaus recognises that information management systems designed for the legacy organisation may not be able to meet the needs of the process management teams in the new organisation. Interim management structures (that can function with currently available IT system outputs) may be required to allow IT professionals time to redesign the organisation’s information management system to be flexible enough to meet changing team needs.

Creating Awareness, Understanding, and Acceptance of the Process-based Organisation:

Starting immediately after the completion of the Strategic Analysis process described above, management must devote sufficient resources to assure that all organisation members, especially key managers, have a full understanding of how a process-based organisation functions. In addition, data based process management skills need to be provided to future process team members. It is not enough to schedule communication and training activities, and check them off the list as they are completed. It is critical that management set behavioural criteria for communication and training efforts that allow objective evaluation of the results of these efforts. Management must commit to continuing essential communication and training efforts until success criteria are achieved. During this effort, it may be determined that some members of the organisation are unlikely to ever accept the new roles they will be required to assume in a process-based organization. Replacement of these individuals should be seen as both an organisational necessity and a kindness to the employees affected.

Implementation of Process Teams:

After the completion of required training AND the completion of required IT system changes, process teams can be formally rolled out in a planned sequence. Providing new teams with part time support by qualified facilitators during the firsts weeks after start-up can pay valuable long term dividends.

Team Skill Development and Continuous Process Improvement:

Providing resources for on-going skill development and for providing timely and meaningful recognition of process team successes are two keys for success in a process-based organisation. Qualified individuals with responsibility for providing training and recognition must be clearly identified and provided with sufficient budgetary resources.

The Hernaus model for transformation to a process based organisation is both well thought out and clear. His paper provides an ample resource of references for further study.

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The Connection between Big Data and MDM

Master Data is information that is critical to your business. This could include contracts, proprietary information, intellectual capital and a whole lot more besides. Because this often reposes in a variety of different places, you need a master data management / MDM policy to control it. That way, you can link it all together in a single, secure, backed up file.

This Sounds Like Big Data

Not necessarily: big data refers to extremely large data sets that are best stored and analysed on a cloud using big technology, in order to uncover trends, patterns and associations often relating to human behaviour. Of course, if you run a niche restaurant your critical master data might be limited to a few recipes and the books you do not care to show your accountant.

The distinction is largely a question of size: think of your master data as the subset of big data that you already have your mind around. According to John Case of IBM this is probably already in a structured format and available to share. He goes on to present a cogent case for using this as a peg point around which to systematise the rest. This is because the average organisation already has master data recording customers? and prospects? behaviour.

Do I Still Need My Master Data?

Yes you do, because real people created it with the benefit of human insight. Retain it as a separate set. Then compare it with the results of big data processing for even richer insights. Two heads are better that one and that goes for data processing too.

Trends in CRM Big Data

Adding data via location-aware devices like smartphones and tablets is adding a new dimension to customer information. We now know where they were when they made the enquiry or punched in the information. Use this geo-location data to hone the way you interact with customers and service their accounts. Do not phone a customer who makes decisions at work when they are at home.

Does My Master Data Belong on a Cloud?

There are a number of ?ifs? to consider. How comfortable are you with your service provider. What would happen if someone hacked their server? There are many advantages to cloud technology. Denizon knows of solutions you can rely on, and makes sure its clients have contingency plans to protect them at all times.

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