Lanner client Nationwide discuss managing demand for automated branch services using simulation
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This document discusses Nationwide's efforts to manage demand for automated branch services. It provides background on Nationwide as the largest mutual in the UK with 14 million members. It then outlines Nationwide's initial attempt to develop a solution using data on availability and customer demand, which showed utilization and customer experience could be improved. The document proposes a structured approach to further develop the solution by gathering additional data on transactions, customer behavior, and devices to better align self-service capabilities with customers' needs and migrate transactions off the counter. The goals are to free up staff time for higher value services and improve the customer experience.
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Lanner client Nationwide discuss managing demand for automated branch services using simulation
- 1. Managing Demand for Automated Branch Services Jay Bourne, Senior Operations Manager, Nationwide (UK)
- 2. A few facts about us UK’s largest mutual Formed in 1846 Top 3 provider of savings and mortgages c.14m members
- 3. Original crowd funding model Owned by members ...not shareholders This means… Stakeholders’ and members’ interests are the same Mainly funded by our members’ deposits Our assets are mainly UK residential mortgages Enables a longer term strategic focus 1 2 3 4
- 4. Multi-account view A few facts about us Internal Self ServiceExternal CashInternal Cash Balance Enquiry Bill Payment Cash Withdrawal MiniStatement Mobile Phone TopUp PIN Change PIN Unlock Cheque Deposit Cash Deposit Balance Enquiry Bill Payment Cash Withdrawal MiniStatement Mobile Phone TopUp PIN Change PIN Unlock Balance Enquiry Bill Payment Cash Withdrawal MiniStatement Mobile Phone TopUp PIN Change PIN Unlock Envelope Deposit 183 Machines located in 178 branches 700 Machines located in 561 branches 487 Machines located in 356 branches Business alignment BACKGROUND Self-Service Capabilities Technology Focus Service focus Customer focus Business focus
- 5. SOLUTION DEVELOPMENT Our first attempt 0.00% 5.00% 10.00% 15.00% 75.00% 85.00% 95.00% 1 3 5 7 9 11 13 15 17 19 21 23 Availability v Customer Served Customer demand Availability Availability Customers Served Service Line Demand Full Service Site Demand Full Service Demand Utilisation and Customer Experience
- 6. Align and define Build Exploit Business Context Retail Strategy Digital Strategy Capability Definitions Output Definitions Define Simulations Reporting Capabilities Vision & Outcome Develop Questions Identify Opportunities Data Gathering Desktop Analysis Service Scenarios Observational Analysis Test Integration Tool Output Target State Function Mode Governance Model Operational Reporting Design Integration Next Steps Confidence Testing Real World Comparisons Usage Cases Enhancement Roadmap Capability Profile Transaction Profile Customer Profile SOLUTION DEVELOPMENT Structured Approach
- 7. STRATEGIC AIM THEMES SOLUTION DEVELOPMENT Align and Define Understand how well the Self Service network meets the demand of its customers for all service lines Provide support services tailored to meet the demand of the customers and the impact on the branch environment and staff Understand how much headroom we have on site to migrate transactions from the counter or introduce new service lines How available are services when customers want to use them? How does demand impact customer experience e.g. wait times? How long do transactions take and how does that vary? What factors impact the transaction time? What headroom exists on the network to support migration of traffic? How can we further reduce the overhead of ATM support on our branch colleagues? QUESTIONS Migrate traffic off of the counter to free up staff time for value add transactions Align Self-service capability with online and mobile service for consistent look and feel across channels
- 8. Transaction timings, distribution of time taken for customer to complete transactions Distribution of customer arrival patterns over the day Transaction mix carried out by branch customer using the site Length of queue before customers begin to walk away SOLUTION DEVELOPMENT Build Access hours Service Configuration Customer Behaviour Number and type of devices e.g. internal cash, internal Self- service, external cash Device configuration, functionality available on devices Number of queues to devices e.g. 1:1 or 1:many
- 10. Next steps • Capacity planning with the physical cash values. • Planning for most effective use of headroom • Cost of service at transactional level by branch • Improvement plans for customer and branch experience • Understand customer experience and used as part of risk based decision on design • Changing support model
- 11. Summary • Disciplined approach makes efficient use of time • Agree the question • The observational insight highlighted some great opportunities • Take your stakeholders with you • Driving to a customer aligned outcome improves team engagement • The relatively complex can be made to look simple • You do what you’re measured on
Editor's Notes
- Introductions Afternoon I’d like to share some of the work we’ve done with Lanner and how have used the predictive simulator to support developments in our ATM operations to understand customer demand and what headroom is available for increased activity and improve our support model.
- A little about nationwide Nationwide is a £203 billion business, the world’s largest building society We began in 1846 with the establishment of the Provident Union Building Society in Ramsbury, Wiltshire Around 700 branches UK Nationwide employs around 17,000 people Look after £1 in every £10 saved We are in the top 3 for savings and mortgages in the UK
- We don’t have shareholders we are owned by our members, those that have mortgages and savings with us. Without shareholders, our focus is providing great service and products to members and it is that service that we see as our differentiator in the market place. We are number 1 for service in the UK on a variety of industry
- A bit of background to our ATM network We have 1400 machine in our branch network processes 95 million transactions a year, dispensing around 4 billion pound We have a couple of different classes of machines with different capabilities that have very different running costs and servicing requirements, these include cash withdrawal and deposit as well as cheque deposit and some account management service. The purpose of the internal machines is to provide additional capacity in branch to handle the simple transactions whilst the external machines provide an income from the servicing of non nationwide cards through what we call the bank interchange fee so for example when a Lloyds customer uses our machine and we receive a few from them Nationwide is currently planning a multi million £ investment in modernising the branch network. With one of the strategic aims being to migrate further traffic on to the ATM as a steeping stone to our online services as well as free up staff time, getting them out from behind the counter to have more value conversations with our customers To achieve this we need to increase the number services we provide on our network including things like setting up and paying bills, being able to view and transfer between accounts in a similar way that it can be done on the online bank and mobile service Th support of the network consists And has its roots in the IT world and is very much focused on hardware uptime, our efforts have been spent industrialising processes like incident, problem and change management as well as focusing on service excellence For a long time we reported our performance in terms of the uptime of the hardware, which doesn’t reflect the impact on customers. More recently we have focused on our customers and how well our service meet there demand at machine level and we are now looking to extend this to site level, because we are also looking at how well we are aligned to the business and the value the network and operation contribute This involves us working more closely with our stakeholders to understand what they want to achieve and put a customer and business lens on what we provide
- Before our engagement with lanner attempted our own modelling We had looked at how we improve availability and the biggest opportunity was the downtime that occurred out of hours i.e. when the branch was closed and we didn’t have access to fix it However when we did the cost benefit we found that so few customers where using the machines that the initiatives didn’t pay for themselves and we couldn’t get any support from the business for them. We started to look more closely at the customer impact of downtime and develop a system at device level that allowed us to estimate the number of customers we failed to serve as a result of any machine outage which we aggregated up to provide a network performance. The business have brought into this and we now report our performance in terms of customers. The next step for us was to start to look at what was happening on a site, explain if you have multiple machines on site that can at times provide resiliency should you experience a failure. We started to look at the site and to develop a view to help us understand how if on service failed on one machine how this impacted the other machines in branch. This involved more detailed understanding of how we understand capacity of a site and how when utilisation increased, customer experience changed. At this stage it was very much a desktop exercise, when we’d finish this we took our findings out to the branch network to see how it stacked up. And we found that it didn’t stack up, where we predicted that resiliency would be sufficient our retail colleagues thought not. Primarily this was the result of 2 things. Our model couldn’t handle the volatility that exists in a number of the components that impact demand And our retail colleagues responded to the situation as it was in front of them with no view of how, events would ( customer experience)unfold. WE engaged Lanner and the predictive simulator to help us understand what was really going on.
- First thing we did was to take a step back and with John and Brain, bring a more structured approach to the exercise we where undertaking and we began planning We talked about our challenge and John talked about the approach we’d undertake. This brought a lot of clarity and discipline to the exercise and helped us get a better handle on what needed to be done as well as engaging with our stakeholders and getting support for the initiative. Initially we discuss what why we are doing this and how we Align and define the requirements Why are we doing this, how does it support the business strategy What are the questions we need to answer Then we looked at the build processes and agreed What level of data do we need, where does it come from. What level of flexibility we would need with in the tool, ( what has volatility and what doesn’t and agree how your going to get it) Agree any assumptions that we are going to make and understand the likely impact on the model Working through this allowed us to start some pieces of work earlier to ensure it came together at the right time To build the tool we used some dummy data to speed up the build process, where we could move quickly enough In terms of Exploitation we looked at What format did we need the output, how would we use it, we back check to the questions we needed answers to check that they would provide the what was expected And at any stage whilst validate progress, we where open to the possibility of loop back and refining the problem / opportunity statement
- Strategic aim of the business Engaged with our stake holders to understand their vision Two priorities for the business Retail strategy –Migrate traffic off of the counter to free up staff time for value add transactions Digital Strategy – Align Self-service capability with online and mobile service for consistent look and feel across channels From this we derived the themes Our customers and how they impacted the devices and the device impacted them Our Branch staff and how they impacted the devices and the device impacted them Our support service and they impacted the devices and the device impacted them And how that would change when new transactions became available to the customer as a result of the migration of traffic of the addition of new transactions We then broke these down into individual questions that we though need to be answered to We referenced this back to our stakeholders to ensure that it worked for them, we had continued to use the branches we engaged when we initial started the look at this
- Once we had defined the question it was about accessing the appropriate data and understanding how we needed to set it up This stage provide some real insight into what our customers where doing and how they experience the services we offered Firstly we thought We needed all the data to have the ability to be modified, this would allow us to do it for individual branches – potentially looking to bolt on the front of a data base to make this easier down stream We need to identify what data would form part of the configuration and what data had volatility, both from the point of being variable in it’s distribution or being random in its frequency we started with the site, we needed to have the ability to define the number and type of ATMs on each site with the capabilities for each type defined. the tool has the ability to run sites with up to twice the capacity that we currently operate to ensure future proofing We then began to gather data on when the ATMs where being used basically How many customers to expect each day and when would they would arrive. We felt that developing arrival patterns on a 15 minute intervals ( to tight and not flexible enough and to far out not realistic) would be a reasonable compromise as a starter for 10. I have used the words arrival, in reality this is taken from actual transaction data on the machine, and whilst this is not the same as customers arrive the lanner team apply some randomising of the data to create variation to simulate real life circumstances. We also need to look at what transaction the customers would carry out, what was interesting about this was the insight into the customers that conduct multiple transaction on the machines and especially on internal machines. This is an area that has caused us to re think how we offer transaction, 23% of the traffic is multiple transaction, so offering a on the front screen an” on screen balance and mini statement” would improve the experience of over 6% of our customers these little insights start to contribute to demonstrating the value the work brings. We then started to gather information on how long our customers took to carry out a transaction. If you talked to the team in the test environment they will tell you they have improved the speed of a transaction to 15 second. That isn’t what is like on the ground. When we started to explore transaction times we had the machines view of the time, what we didn’t have was the customer walking up, getting the purse or wallet out, marshalling the kids, etc. so we need to conduct some observational work to see how it actually works The observational insight probably gave us our biggest win. We found a number of issues with transactions that we hadn’t appreciate. 30% customers putting cheques in wrong and have to re present them despite what we thought where good graphics. Cash deposit notes being returned, confusing the customer, which caused the branch staff to become involved and eating into there time. We have taken those learning and have started a program to improve those , which will reduce the impact on customers and staff as well as improve capacity.
- A short video This displays a view of one of our branches laid out as most of stakeholders would recognise its showing how our customers come into our branches and use our services The display is really useful for demonstrating to stakeholders, executives or branch staff discussing design decisions or how different approaches might impact customer behaviour When we talk to our retail colleagues now the conversations are very different. They focus on the experience the customer has How many customer have to queue and for how long When the branches are experiencing periods of stress. Typically over the lunch period branches get busy and whilst one view might be that the ATMs are busy for 1hour a day. Another is that actually 40% of you customers had to queue with and average wait time of 6 minutes. This drives a different conversation and focuses us in solving problems in different ways. Proportional response across response teams – Branch, engineers sla development How machine perform when a service line fails – triage customer and maintain capacity levels The design process. Modelling queue configurations as part of the design – different machines must have different queues – story of Cheapside Design risk rear and front loading machines The cash forecasting team are now using it to support a cost challenges. reviewing which machines have better resiliency and reducing replenishment frequency, increasing the risk of running out of cash but in the knowledge that on the sites they are trailing on have resiliency on site and so reducing the impact on customers. That’s on going. Modelling new services Headroom and the impact. Passbook introduction. Impact Investment profile for future migration, and what provides biggest bang for our investment We now have the ability to feed in all forecasts to predict with a level of confidence the number of devices needed on any site. and we can have an risk based discussion when space is a problem All of this is easily demonstrated and facilities different outcomes from our engagement with the stakeholder community be it Retail, designers or suppliers and support team. Getting by in because confidence levels on both sides are so much We’ve been back to the branches and helped them manage there queues, potential
- Capacity planning with the physical cash values - driving counter traffic off the counters means we need to understand how the devices will coupe with the physical volume of cash so we have plans to look at how we can introduce the cash volumes to verify the servicing requirements post migration We are also looking at Recycling technology Currently the deposit technology used means that deposits are removed when the machines are service by the staff. We have the opportunity, as part of the investment and machine refresh to consider recycling technology, this means that instead of removing the money we can dispense it to other customers, reducing the cost and time of servicing and that of cash logistics. Modelling this will give us a really good idea of tipping points and where it will work Planning for most effective use of headroom – we have a number of options for migration of transactions, including, with our exist estate what can be accommodated and what needs in vestment Cost of service at transactional level by branch – The transaction costs at a branch level start to tell us if we have the right number of devices and how we can balance up counters and devices and what is optimum for the transaction mix on that site Improvement plans for customer and branch experience- reliability Cash deposit monitoring, templates, - - - improve user interfaces for inputting cheques and how Understand customer experience and used as part of risk based decision on design, we have design options in smaller branches, rear and front access, using the tool to set parameters to help understand the impact of failure is to high to --- - Changing support model - - - Branch SLA, engineering SLA out of hours maintenance not to improve availability but to reduce the impact on staff, especially where we have machines that are maintained in the banking hall The initial piece of work has caused us to ask more question and provide real momentum in a number of areas to develop our thinking and where we can get value from the work done. Not all of it will involve the predictive simulator but some will We’ve already touch on the opportunity to improve the customer interface and reliability of certain transactions. the business case for prioritisation has more weight when we can demonstrate how we can improve capacity through the improvement of transaction times and benefit, in some cases creating capacity through improving performance rather than addition machines We have started to embed the use of the tool in the design process, identify sites that are on the edge of service expectation and discussion alternatives to how we might ensure that access for maintenance is improved We are no looking at how we can model the physical cash that is deposited in our devices and how if we use recycling technology rather than asking the staff to Our support model is changing with more emphasis on how we can be more proportional about how quickly we ask the support teams to respond. Some of these will be through the simulator some will require other analysis tools to deliver them
- In wrapping up a couple of things I’d call out Disciplined approach makes efficient use of time Know where you want to go, you wont know when you get there so having plan is vital So an appropriate methodology is vital to the success of the project and how well it align to business outcomes Agree the question Linking the question straight through to the strategy is great for the engagement of your stakeholders The observational insight highlighted some great opportunities The data gathering provided some real wins, spending the time to observe what was going on has given us some real nuggets to improve our services and challenge how we go about ensuring we develop and monitor service. Get off the data page and get out to where it is happening Take your stakeholders with you Because of the thorough job that we’ve done and taking our stakeholder and team on the journey confidence in the output is high and recommendation seen in a more positive light. Driving to a customer aligned outcome improves team engagement Measuring and aligning our operation to business based outcomes makes it much easier for the team to understand it’s purpose and increases levels of engagement and productivity through out the team. The relatively complex can be made to look simple This is one of the real strengths of the tool, I might struggle to convey the information here. A picture tells a 1000 words. Not sure how many a video tells You do what you’re measured on Get the metric right for any activity and it will drive the right outcomes – this started all because we moved from uptime to customers served and our wanting to answer that question as accurately as possible Thanks you for your time. We now have the ability to feed in all forecasts to predict with a level of confidence the number of devices needed on any site. and we can have an risk based discussion when space is a problem. We can model different configuration types to understand if we should look at alternatives We understand how we need to respond to an outage based on the impact on our customers and our branch staff. The opportunity to exploit the information to make cost savings we can take more risk on sites and cash replenishments We’ve been back to the branches and helped them manage there queues, potential Insight and learning into our service and customer experience invaluable for us to understand our customers experience and make a real difference Driving to a customer aligned outcome provides real clarity of purpose for the team to get behind. Which drives a higher level of engagement and performance