Using Pull Systems to Optimise Work Flows in Call Centres

When call centres emerged towards the end of the 20th century, they deserved their name ?the sweatshops of the nineties?. A new brand of low-paid workers crammed into tiny cubicles to interact with consumers who were still trying to understand the system. Supervisors followed ?scientific management? principles aimed at maximising call-agent activity. When there was sudden surge in incoming calls, systems and customer care fell over.

The flow is nowadays in the opposite direction. Systems borrowed from manufacturing like Kanban, Pull, and Levelling are in place enabling a more customer-oriented approach. In this short article, our focus is on Pull Systems. We discuss what are they, and how they can make modern call centres even better for both sets of stakeholders.

Pull Systems from a Manufacturing Perspective

Manufacturing has traditionally been push-based. Sums are done, demand predicted, raw materials ordered and the machines turned on. Manufacturers send out representatives to obtain orders and push out stock. If the sums turn out wrong inventories rise, and stock holding costs increase. The consumer is on the receiving end again and the accountant is irritable all day long.

Just-in-time thinking has evolved a pull-based approach to manufacturing. This limits inventories to anticipated demand in the time it takes to manufacture more, plus a cushion as a trigger. When the cushion is gone, demand-pull spurs the factory into action. This approach brings us closer to only making what we can sell. The consumer benefits from a lower price and the accountant smiles again.

Are Pull Systems Possible in Dual Call Centres

There are many comments in the public domain regarding the practicality of using lean pull systems to regulate call centre workflow. Critics point to the practical impossibility of limiting the number of incoming callers. They believe a call centre must answer all inbound calls within a target period, or lose its clients to the competition.

In this world-view customers are often the losers. At peak times, operators can seem keen to shrug them off with canned answers. When things are quiet, they languidly explain things to keep their occupancy levels high. But this is not the end of the discussion, because modern call centres do more than just take inbound calls.

Using the Pull System Approach in Dual Call Centres

Most call centre support-desks originally focused are handling technical queries on behalf of a number of clients. When these clients? customers called in, their staff used operator?s guides to help them answer specific queries. Financial models?determined staffing levels and the number of ?man-hours? available daily. Using a manufacturing analogy, they used a push-approach to decide the amount of effort they were going to put out, and that is where they planted their standard.

Since these early 1990 days, advanced telephony on the internet has empowered call centres to provide additional remote services in any country with these networks. They have added sales and marketing to their business models, and increased their revenue through commissions. They have control over activity levels in this part of their business. They have the power to decide how many calls they are going to make, and within reason when they are going to make them.

This dichotomy of being passive regarding incoming traffic on the one hand, and having active control over outgoing calls on the other, opens up the possibility of a partly pull-based lean approach to call centre operation. In this model, a switching mechanism moves dual trained operators between call centre duties and marketing activities, as required by the volume of call centre traffic, thus making a pull system viable in dual call centres.

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4 Reasons Why You Might be Missing Out on Energy Savings…

?well your company actually, although for many small-to-medium businesses it boils down to the same thing. Governments usually lag behind in terms of innovation but are beating us hands-down when it comes to going green. I have heard that private sector energy savings average less than 1% per year and I for one would not be surprised if that were true. So what is causing this rot, when we started out so enthusiastically? Here are four possibilities for you to mull over.

  1. Your Team is Unevenly Yoked ? A pair of mismatched horses cannot pull a wagon in a straight line any more successfully than a business team can achieve its goals, if there is no agreement on priorities. While your sales team may be all for scoring green points against your competition, your accountant has a budget to balance and your operations department just wants to get on with the job.
  1. Energy?s not in Focus ? The above may in part be due to production goals you set your department heads. Energy is not nearly as greedy as raw materials and human capital. If you tell them to cut 5%, where do you think they are going to look first? You need to put energy savings up there, and agree specific targets as you do with other primary goals.
  1. Your Equipment Could be Over-Spec ? It is a very human thing to put more food on our plates and buy faster cars than we need. Only a few generations ago our ancestors lived through feast and famine, and the shadow of this still influences our thinking. Next time you buy equipment sit around the table and agree the decision criteria together. Then stick to them and repel all attempts at up-selling.
  1. You Are Delegating Too Much ? Delegation is part of company culture, or if you prefer the collective way of doing things. If you delegate something completely it is akin to saying I do not care much about this, make it happen. Energy saving is a financial and moral imperative. The fact the oil price is down does not mean there is no place for sustainability on your desk (and the price is likely to be up again soon).

Governments succeed in saving energy (whereas businesses often do not) because governments have a crowd of stakeholders beating down the door and demanding progress. As business owners we are more likely to do the same when the pressure is upon us, and that pressure surely has to come from us.

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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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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