The Five Myths of Effective Customer Service Models
Introduction
As we look around customer sales and service operations we see many businesses striving to find a better way to organise their work and people. They are in search of organisation models that make them more efficient and effective. Typically they are looking for:
Greater first contact resolution of customer issues and a positive experience from the interaction
Minimised customer effort in any interaction
Increased conversion and lead capture where appropriate
A more timely response for the customer
A minimised handle time for the company and customer (customers are time poor and have better things to do than queue and sort out issues the company has created)
A short learning curve for new hires but a range of attractive career options to make people want to stay, and
A model that can flex as the business changes
That sounds like a big ask. In response, many different organisational models have been
proposed as ways to achieve these outcomes. You may have heard claims like:
“Skill based routing reduces learning curves and delivers better resolution”
“Knowledge tools enable our staff to answer every type of customer query”
“We are a truly blended contact centre and our agents can handle calls, emails and correspondence”
‘’Only by blending front and back office work or sales and service can you have a highly efficient model’’
‘’We are organised around customer segments and therefore deliver better service to our valued customers’’
Many of these claims are associated with different technical solutions but in our experience the hype is not matched by the reality. So let’s explore the five mythical models and look at the cold hard reality before we set out a more robust way to tackle the issues.
The Myth of Skill Based Routing
The theory goes that by breaking down work into narrow skills you create jobs that people can easily master. In theory this shortens the learning curve and should ensure high rates of resolution. That’s the theory. Now let’s look at the reality.
Spaghetti Junction
One Telecom company we know has created 67 skills across its fixed line, internet and mobile products.
So each skill is discrete and should produce high rates of resolution. Unfortunately this company is famous for poor customer service and has become the butt of jokes across the industry.
The first problem they created is identifying which skill the customer needs.
Navigation Effort
Rather than low effort, the complex speech engine that customers have to navigate is the source of customer hatred and fear. Many customers spend minutes in the engine prior to reaching someone and experience dead ends and other forms of failure. Worse still, the speech engine often doesn’t match people correctly to their need. Unplanned transfer rates across the skills are very high creating high effort and unsatisfying experiences. Customers can’t articulate their problems well enough in the company’s language to reach the right person.
First Call Russian Roulette
Even when they do reach the right person, the problem may be very simple or it may be very complex. So a new agent fresh out of training and trained in their one narrow skill, such as mobile billing, may get a really ugly and complex incorrect bill call on their first minute out of training. These skill models based on products or functions rarely isolate complexity. Each skill is likely to have a mix of very simple and very complex calls, so inexperienced agents aren’t protected in the way management expected.
Strategic Mismatch
This model also ew in the face of the Telco’s customer strategy. This strategy was aimed at selling more products and services to its customer base. Its ideal customer had all its products. So the more valued customers were far more likely to ring with issues spanning multiple products and services. Yet they would have to navigate across a range of different specialists to be served. The skill model also meant that agents were under skilled in being able to cross sell other products and services.
Rostering and Management
Models like these are hard to manage. Rather than planning and rostering for one centre, this Telco was, in effect running 67 call centres, one per skill. Rather than leveraging the scale and size of its workforce, the skill model had created silos that frustrated the customer and delivered poor experiences.
Staff were also angry that for some of the day, a central management function “ flicked their skill” to answer a call on a line that they did not know, purely to diminish the queue developing there. The result: a poor conversation and a transfer to a queue anyway.
So our issues with skill models are that they create complexity of navigation for the customer, are complex to manage and don’t isolate complexity effectively. One successful approach, described later, is to really isolate complexity within the organisation model and to do that we’ll need to help the customer work out the complexity of their problem. Later we’ll explain how.
The Myth of the Knowledge Tool Enabled Super Agent
Universal Know How?
At the other end of the spectrum from the skill based model, is the idea of creating “super generalists” with access to knowledge tools to help them solve most problems. The idea here is to build the knowledge and complexity into the tools and put this at the fingertips of generalist type staff.
For organisations with lots of simple problems, of course this can help and these tools are an effective way to enable reasonably inexperienced staff to solve many easy problems (providing the knowledge tools are well built and maintained). But the more complex the systems, products and services become, the harder this is to achieve. Even the well known “Tim Tam” biscuit has developed a more differentiated product design with different features, benefits and market positioning.
In the Financial sector product splitting and complexity has proliferated, and will continue to do so. Merger and Acquisition activity has compounded this problem again. Complexity In our experience, complex contacts are often about situations and problems that are more unusual and harder to predict. In many call centres the 30% of complex queries account for over 60% of the work .
In the example below, calls under six minutes were 73% of the volume but only 41% of the work.
So these knowledge based models can still deliver poor customer experiences where customers are put on hold or resolution of complex issues doesn’t occur. The problem is that it is hard to populate a knowledge tool with scenarios that the company hasn’t observed frequently or that result from the complexity of products and services.
Self Service Undermines the Model
What we have observed is that, the more complex the company and its services, the less likely these super generalist models are to work. The problem is made worse as companies succeed in migrating customers to self service. Typically self service handles simple enquiries and transactions. This leaves the human interaction channels with increasingly complex interactions.
Customers self serve on easy things and call for help when things go wrong or don’t work as they expect. The knowledge systems start to fail the front line in these scenarios as they can’t predict answers to complex scenarios and issues. For the knowledge systems to work well, they must also be quick and involve minimal navigation. So as the complexity rises, they become less useful in providing quick answers for the customer.
Best Agent Utilisation
There is a secondary problem with the generalist model because it wastes the skills of the best agents. An agent with five years of experience is as likely to get a simple call as someone straight out of training. Equally, the new trainee is as likely to receive, and flounder, on a complex problem.
This almost always creates a long call, hold periods, as well as escalations to support staff or team leaders. New agents still need lots of extra help and customers often get poor experiences as a result. So this generalist approach is often not efficient for the customer or company. If a company tries to train new staff in all possible scenarios, as a response to this, this leads to very long induction and training periods, and is very expensive.
So, once again we need to find a model that gets simple problems to those with the least experience, but leverages the knowledge of our best agents. A generalist model doesn’t do that but models we’ll describe later do.
The Myth of Blending Contact Mediums
All Channels to All People
The theory goes that it is far more efficient if front line staff can handle multiple contact mediums – calls, letters, emails and it helps balance peaks and troughs in each area. Some technology companies have been pushing this concept for a while in an attempt to sell their products.
The problem we find with this theory is the skills are different. Great authors do not always perform well on radio and customer service mediums are similar and yet somehow we expect front line staff to have the skills to jump mediums and perform in all mediums.
Workus Interruptus
Having tools and processes to make each job easier is a help but doesn’t guarantee success. In one call centre that also tried to process emails we found that each agent handled each email 2.5 times on average because calls regularly “dropped in” and interrupted their work. Not only was that less efficient than separating out these skills, but we observed serious quality issues in both channels.
Productivity Miasma
Merging channels can make managing people harder because measurement of things like blended productivity is much harder – and can lead to conflict and management drag to try and solve this issue for the staff members. This can actually dis-incentivise team members rather than motivate them for task completion. If someone is dedicated to emails or calls or letters it is much easier to set a target and measure against it. With integrated jobs, visibility is lost.
Hybrid Models
However, we’re not arguing totally against the idea of creating what we call “hybrid teams” of people that can move between the different roles. These models can work well particularly if we can leave people in one work type at a time or only interrupt one mode of working occasionally. When this is the case, we have developed clear structure and roles coupled with clear real time management rules to protect the model, and allow for maximum utilisation. What we argue against is the concept that staff can flip flop frequently between different channels and be efficient in doing so. We’ve all experienced the annoyance of being interrupted by the phone when doing something else. Why would we design a service operating model based on constant interruption?
Hybrid models work even better if we can isolate work by complexity (as we’ll describe later) so that someone doesn’t have to make the jump from a really complex letter to a simple call or vice versa. The skills become more transferable across channels if we’re handling similar types of problem but unfortunately the solution vendors don’t add that caveat. If well managed, these models can also help front line staff assist customers to make the best use of different channels because the staff understand them better.
The Myth of Blending Contact and Administration
Recently a major strategy consultancy wrote to the boards of many companies claiming that call centres were always inefficient and only models that mixed back and front office work could solve the problem. Firstly there is a key assumption that reasonably large scale call centres and admin areas can’t in themselves be highly efficient. We have seen many centres and functions with 30 people or more that run at very high rates of occupancy and don’t have these “gaps in utilisation” that this strategy company claimed. But let’s investigate the idea anyway.
Profiles are Different
As with the blended contact medium idea, one problem is that many people aren’t cut out to do very different skills that each job demands. When we work with call centres and back offices we find very different types of competencies are required, resulting in differing profiles being more successful and productive. Call centre profiles generally have better interpersonal skills and deal with the complexity of random call arrival. That’s a very different mindset from the profile of a person who can have very high attention to detail, high accuracy, and high through-put of a repetitive back office task. So expecting to find people who can switch easily from one to another, and maintain effectiveness and productivity in both disciplines is a lot to ask for! Sales and service are also much harder to mix than most companies recognise. There is a body of psychological research that has shown that the mindset of sales staff and service staff are different. That isn’t to say that sales staff can’t deliver great service and service staff can’t sell but it is just harder than it looks.
Measurement
As with the blended channel example, it is much harder to measure people who are being interrupted by calls or have to jump between types of work. Even the management tools, like workforce planning products become less effective when we blend work in this way. Call centre planning software manages random arrival whilst back office tools like to manage work on hand. Measuring one person on service quality, productivity, sales conversion and compliance starts to lose the power of simplicity. We often hear front line staff say, ”I’m not sure what they want me to do”. We have succeeded in blending this work but staff need a very clear practice set to work within. Without one they try to sell at inappropriate times (when there is a queue) or ignore service and retention opportunities.
Our final critique of this blended model is that it ignores different levels of off-shoring potential. Customers don’t know, these days, who processes their application or handles their claim. There should be few issues in off-shoring that type of back office work. But culture and accent issues are much harder to hide in call channels or those involving complex correspondence.
The Myth of Segmented Service Models
The theory goes that if we dedicate our best staff to the most valuable customers, they get better service. That sounds great but there are four problems with this model:
The highest value customers also have simple enquiries which waste the time of highly trained staff.
The smaller the segment and group, the more we have to under utilise these better people in order to guarantee the higher service level.
Customers don’t always access the organisation in a way that identifies them as valuable, so they end up in the mass market or other channel anyway. Even if we give them a special number, they may call an old one or they may not ID themselves so we cannot place them in the segment they belong.
Most valuable customers start their relationship in another segment. So a highly segmented model may protect today’s valuable customers at the expense of tomorrows.
This model misses the point that we can offer better service to valued customers without realigning the whole operating model. For example a valued customer can be promoted to the front of a call centre queue and no one else will know. Similarly a valued customer ought to be shown greater tolerance on certain fees or other business rules and offered more options and choices by any member of staff. We have shown that a well designed operating model doesn’t need to segment because it can offer great outcomes to all customers. Then we don’t need to worry who is valuable now or who will be in the future.
Truth: The Model That Fits Your Business
Tailored to Your Business and Customers
Some people think that our success in helping companies develop new models and the results we have achieved are all based on the one model which has become known as pebbles and boulders. The basic idea here is to split work by complexity and get complex work to the most experienced staff. The interesting thing is that this is also a myth! Every model we have developed for our clients is tailored to their specific business strategy, product and geographical framework.
That is why they have worked so well. The idea of splitting work by complexity may have been common but the way this has been achieved is different in each instance. For example one client had two call centres. The first dealt with customers directly, the second with intermediated brokers. The model we developed for each was very different. Both had a two tiered approach, but in the intermediary model only complex complaints were pushed to the second tier. What they do have in common is in our approach to design five key elements of the operation simultaneously and align them for the type of work involved.
PRISM: Practice, Resourcing, Indicators, Structure and Management
In short we know that effective operating models, whether it be a Contact Centre, Email processing service team, Branch sales office or Administration area, combine five key elements that we refer to as PRISM:
In order to design an effective model from these elements we recommend:
Understanding the nature of the work. This means diagnosing how complex the work is, what makes it complex, how long different types of work take, their criticality, the customer experience that is desired, the capabilities of staff and many things. To design an effective model requires a detailed diagnostic of the work, organisation, technology and people in any operation. We have a diagnostic process to do just that.
Working with staff to design how practices and a new structure can be aligned and consider all the elements of the model. We don’t just assume that a new structure will solve the problem, we assume that call taking practices as well as processes can be improved and technology exploited better at the same time.
Considering the company and customer strategy, self service and other strategies. How do they want customers to be treated? Which channels would they like customers to use? How successful has channel migration been and what does it need to be?
Understanding the current and potential workforce. If the types of people working in the business are changing then we need to build that into any model design.
Understanding the technologies available to support staff. Are systems simple or complex to learn? Is there effective knowledge support and which new systems are planned?
So designing an appropriate solution is not easy. However, the results have been spectacular:
Case Example
A Wealth Management business had divided its service teams along product lines. Each was a separate skill grouping with very little cross skilling. This meant that each team was also sub scale, with low utilisation in many periods of the week and high cost. The company battled between the teams being either too big, underutilised, or too small to handle the work.
Large annual peaks made the problem even harder. There was also no obvious career path for staff. Furthermore performance was very variable within the teams and team leaders spent all day solving problems and handling escalated work.
We used our PRISM methodology to create an operating model where the work was split by complexity across the teams. New practices changed the way the business handled every major contact type and aligned to this structure. It included new ideas like the first line agents having questions to figure out the complexity of calls.
This model created scale immediately in both layers and inexperienced staff no longer fumbled through hard problems. Performance became far more visible and now staff had a range of career options. Team leaders now had the time to coach and focus on performance with a framework to coach against from the revised practice set.
The company measured improvements of over 25% in overall productivity and reduced customer wait and end to end transaction times. Customer satisfaction improved dramatically and staff retention improved. The model improved the business on every major measure. It made induction of new staff faster and easier and simplified planning and managing.
Conclusion
It’s easy to be seduced by the myth makers who promote a single operating model answer. We think the only way to deliver sustained improvement is to understand your customer needs, the work involved and its complexity. Then design a model that aligns work to experience and where practice and organisation structure are in harmony.
Don’t let one dominate idea dominate your thinking.
Time and again we have shown that this more holistic approach works because these models have delivered a minimum of 20% benefits every time with as much as 50% in some instances.
Better still, none have needed any kind of software investment or major capital injection to transform into a customer centric centre of excellence.
