Best Practice Insight - National Express delivers six-figure revenue benefits with a self-service BI platform
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mwd advisors Best Practice Insight National Express delivers six-figure revenue benefits with a self-service BI platform Helena Schwenk Premium Advisory Report May 2014 This report examines the UK Coach division of National Express’ initiative to deploy a self-service Business Intelligence (BI) platform based on technology from QlikView to help the company report on performance and drive real competitive advantage and customer insight for the business. MWD case study reports are designed to help organisations considering or actively working with analytics software understand how others have worked to obtain benefits from analytics implementations, and how they have worked to overcome challenges that have arisen along the way. All MWD’s case study reports follow a standard model, and are researched using a standard process which is driven by senior MWD analysts. This report is published as part of MWD Advisors’ Analytics research program. You can find out more about how to access related research at http://www.mwdadvisors.com/ec/membership.php. MWD Advisors is a specialist advisory firm which provides practical, independent industry insights to business analytics, process improvement and digital collaboration professionals working to drive change with the help of technology. Our approach combines flexible, pragmatic mentoring and advisory services, built on a deep industry best practice and technology research foundation. www.mwdadvisors.com © MWD Advisors 2014
Analytics case study: National Express 2
Case study key facts
Organisation National Express UK Coach Division
Industry Transportation
Current BI goals In late 2011 National Express UK Coach began an initiative focused on
three core goals:
Developing and rolling out a more flexible and self-service
Business Intelligence (BI) environment that enables business users
to analyse, drill down and report on their own data.
Providing access to different types of customer-focused data and
metrics so the company can sustain a more customer-centric
view of performance to meet its corporate promise of delivering
better customer service and cost efficiencies.
Developing new reporting applications that provide greater
customer insight and are aligned with how the company needs to
report on business performance.
Current approach National Express’ BI environment comprises a mixture of standard
reports and self-service applications that support around 70 users across
the business in areas such as sales, marketing, business development,
pricing, PR and finance. The BI team is currently focused on a number of
initiatives including:
Rationalising its existing portfolio of legacy Excel reports and
migrating them onto its new QlikView BI platform.
Developing and releasing new BI apps in areas such as route and
network optimisation, competitive and marketing intelligence, and
supplier performance.
Maintaining and growing its BI community by holding monthly
QlikView café sessions and allocating business partners who are
responsible for supporting and engaging users.
Outcome The ability to access more data within a self-service BI
environment and the addition of new reporting applications has
brought many benefits to the business. In monetary terms the
project is estimated to have delivered six-figure revenue benefits
annually by being able to respond to market changes by
analysing market data as part of assessing National Express’
value for money. Likewise the company has seen improved
customer service and value through the analysis of sales
compared with routes that help identify and deliver network and
route efficiency. Finally, by changing to a self-servicing BI
environment National Express has been able to release
development time from the BI team allowing them to work on
customer-centric focused reporting apps.
© MWD Advisors 2014Analytics case study: National Express 3
BI tools and suppliers QlikView Business Discovery platform version 11.20
used
Company background
National Express Group is a leading transport provider delivering services in the UK, North America,
Germany, Spain and Morocco.
Headquartered in Birmingham, UK, over 800 million journeys a year are made on National Express
buses, trains, light rail services and coaches. At the end of 2013 the company employed 42,000 people
across six countries, operated over 25,000 vehicles and generated £1.89 billion in total revenue.
In the UK the company has three divisions: coach (the focus for this case study), bus and rail services
that operate across the country. The coach division runs the largest scheduled coach network in the
UK and operates high frequency services linking around 1,000 destinations. In 2013 the division
generated £263.5 million in revenue, representing a 3% year-on-year increase.
Project background
Back in 2011 the coach division of National Express sourced its BI information via a set of ‘glorified’
Excel reports powered by a SQL Server database. The suite essentially comprised a series of pivot
tables and worksheets that reported on sales revenue information for sales, marketing, business
development, PR and finance users.
Despite having a good rate of adoption in the business, many users felt the suite did not support them
adequately and it was becoming increasingly ‘unfit for purpose’. Apart from a lack of automation in
report production, and some duplication of reports and data, one of the key criticisms levelled at the
suite was its inflexibility. This typically manifested itself in two ways:
Firstly, ad hoc report requests or changes to existing reports had to be channelled through a
small one-person BI team. With such limited resource it often proved impossible to manage
all incoming requests in a timely manner and as result many users experienced backlogs and
delays in getting the information they needed.
Secondly, some business users, specifically those in the commercial team, had data-driven
analyst roles and wanted a greater degree of autonomy in which to manipulate and report on
the data themselves. Frustrations grew because the current BI suite was not able to facilitate
this self-service mode of operation; instead, users were limited to the degree by which they
could interrogate and analyse the data.
Against this backdrop a new Managing Director, Tom Stables, was appointed to the UK Coach
division in early 2012. In his new role Stables placed an increasing focus and emphasis on data-driven
decision-making, data analysis and customer insight. His vision was that the organisation must sustain a
customer-centric view of performance to complement its existing transactional view so it could meet
its corporate promise of delivering better customer service and cost efficiencies. Up until this point
the company’s data warehouse only really held sales data; bringing more customer-related data on
board was deemed an essential approach to gain further insight and understanding of the customer
journey.
As a result of all of these developments the general consensus in both the BI team and business
community was that a more flexible BI suite with self-service capabilities for business users was
required. Not only would this provide greater data analysis flexibility for users but it would help
release development time from the BI team so they could concentrate on developing new applications
aligned with how the company wanted to report on performance. Similarly, as a consequence of these
factors the BI team set out to develop its BI strategy to take into account the need to broaden the
range of data in the warehouse as a way of building out and enriching the customer view and
providing a more consistent and single source of customer intelligence.
© MWD Advisors 2014Analytics case study: National Express 4
Implementation characteristics and current status
Today National Express’ QlikView platform has around 70 users in a range of functional areas
including sales, marketing, business development, pricing, PR and finance. In addition to users at the
company headquarters in Birmingham, there are a further 20 coach station managers based around
the country.
The implementation of QlikView and its subsequent rollout to various parts of the business has
concentrated on two main streams of work. Firstly, the BI team focused on rationalising and migrating
the organisation’s existing legacy BI reports from Excel to QlikView. By mid-September 2013 the BI
team had transitioned all of its sales reporting to QlikView, and the following October the company’s
sales reporting was brought over onto the new platform. This means that today around 80% of the
organisation’s legacy reports are now available within the new BI environment.
Secondly, the team (with the addition of extra resource) focused on developing and releasing new
QlikView applications to support various different business functions and needs. The first app,
released in August 2013, enabled the pricing department to determine if each route offered
customers value for money based around changes in the market. This app proved very successful
since it delivered functionality and a level of detail not previously available before; not only did this
enhance its value to the business but also helped build momentum and buy-in to the QlikView
approach.
Other apps have consequently followed including apps for:
• Analysing service and network performance for both customers and suppliers.
• Combining sales data with Google maps to provide analysis of routes and sales to improve
the efficiency of routes and network.
• Analysing supplier performance against service level agreements to identify opportunities for,
amongst other things, contract negotiations.
• Analysing customer satisfaction across a number of key factors weighted according to
importance to the customer, such as value for money, for example. Previously this
information was collated in part manually and was only available on a monthly basis.
• Helping finance users reconcile management information sales figures within QlikView against
its operational financial systems.
The BI team continues to roll out more apps and has set itself a goal of releasing on average one app
per month. A number of these apps are already in the planning or development phase: one focus area
is around the analysis of punctuality metrics and drivers through its linkage with the Coach Tracker
app that allows customers to know where their coach is at any point in time. At the moment the
reporting of this data is provided through a third party, so the eventual aim is to bring this data into
QlikView and combine it with customer satisfaction data in order for users to perform root cause
analysis.
Similarly, another app will aim to bring customer satisfaction data into QlikView to help users analyse
more about the underlying causes of good or bad customer experiences. The longer term perspective
is to incorporate social media monitoring and sentiment tools and bring social conversations into
QlikView. Likewise, National Express wants to include HR metrics within QlikView so it can analyse
business performance in the context of metrics such as staff turnover, training and so on.
The approach
National Express took a phased approach to developing and rolling out its QlikView platform. The
first phase of the project started in the May to June 2013 timeframe and focused on developing,
communicating and gaining buy-in from the executive board and key stakeholders to the
organisation’s new BI strategy.
© MWD Advisors 2014Analytics case study: National Express 5 This strategy was aligned to the overall corporate vision and values (outlined in the Strategy section of this report) and centred on explaining both why and how the coach business should shift from using data to not only run the business but also to seek competitive advantage from its use. A key element of securing buy-in focused on communicating the advantages of its self-service BI approach to each part of the business. This was a crucial part of the project since the BI team had previously undertaken a QlikView project only for it to be eventually abandoned due to lack of business commitment. Keen not to make the same mistakes again, the team went about the project in an entirely different way, with people engagement and buy-in specifically given a much higher priority and emphasis for the project from the outset. One strategy used to garner buy-in was to target the first QlikView application on something the business really needed, but equally importantly, hadn’t had before – the team knew that if it just replaced aspects of BI functionality there was a high chance this would jeopardise their ability to gain consensus and buy-in to their approach. In this case the BI team (in consultation with the business) chose a new application to support pricing sensitivity information and analysis. Once the appropriate buy-in and sign off had been achieved an RFI was sent to Qlik and two other BI vendors. Qlik was chosen by virtue of its ability to show value to the business. The vendor was, for example, able to quickly prototype an application using the company’s data and demonstrate the ease with which it could support drill-through and querying flexibility using the QlikView in-memory Associative Model. The next phase of the project kicked off in July 2013 and focused on working with Qlik partner, Data Technology, in training the BI team on the QlikView platform to build up their knowledge and skills. In total the company used around 20 days of consulting. Five of these days were used for a technical training boot camp enabling team members to get an in-depth overview of the technology in order that they could support their own app development process. Shortly afterwards in August, the team was able to release its first pricing sensitivity app and it has been releasing apps (as outlined in the Implementation section) ever since. In tandem with this development work the team has also focused on rationalising the organisation’s current Excel reports and migrating them to QlikView. In terms of working methods, the business and BI team work on a collaborative basis during the development and implementation phases of a QlikView project. The requirements gathering phase, for example, is a joint process between the business and BI team where both parties ensure requirements and changes are validated every step of the way. Similarly, User Acceptance Testing is a very iterative process whereby issues and resolutions are fed back and communicated on a continual basis. In fact, the speed at which changes and suggestions are implemented by the BI team has helped increase momentum and buy-in behind the project. Previously changes to reports could take weeks, and the responsiveness of the BI team together with the agile nature of the BI tool is seen as a huge benefit for the business. Going forward the next big development project for National Express will be to incorporate and analyse more of the company’s CRM and clickstream data within QlikView; this is expected to take place in the next six to nine months. Strategy National Express launched its group-wide company vision and values in 2010, outlining its ambition to “earn the lifetime loyalty of customers by consistently delivering frequent, high performing public transport services which offer excellent value”. This vision is underpinned by a set of core values comprising Excellence, Safety, Customer, People and Community. Both the vision and core values are used to guide how National Express operates as a business and prioritise what it focuses on. © MWD Advisors 2014
Analytics case study: National Express 6 In line with this corporate approach Tom Stables has encouraged and directed the coach division to embrace a customer-centric culture though these vision and values. This has meant changing the metrics with which the coach division monitors and measures business performance by building KPIs around each value in line with what customers also say is important. For example, customer satisfaction is a KPI measured across the National Express Group and is also used to set strategy and improve services in line with customers’ expectations. In this context the company’s BI strategy takes a top down view by setting out its high level aims and objectives in the context of the overall corporate strategy. Its vision centres fundamentally on the need to not only use data to report on performance but to leverage it to drive real competitive advantage and insight for the business. Having strategic level buy-in to the BI strategy from Tom Stables has also helped spur adoption and build awareness of the tool among the group board and wider business. Having undertaken QlikView training himself, Stables was able to see for how the first pricing application was delivering value back to the business; this consequently helped bring more business users and managers on board as their need to understand what new data was available and how it was being used quickly developed. Organisation and people The BI team sits within the business planning function at the coach division of National Express, alongside other teams including commercial finance, pricing implementation for customers, and the Duplicate planning team (which looks at demand planning for coaches). The team has one BI lead and two BI developers. Initially there was only one BI developer but the Business Planning team secured an extra resource in the early phases of the QlikView rollout based on evidence of growing demand and increased buy-in from the business community. BI Manager, Frank Kozurek, takes an active role in not only running the team but also in stakeholder management and engagement. This was especially important during the early stages of the project when securing buy-in and commitment to the project was key to its future success. During this work the team leader was responsible for communicating and engaging with the executive board about the BI vision, strategy and enabling QlikView technology. Part of Kozurek’s day-to-day remit also involves building and maintaining the BI community where he is responsible for allocating owners to each of the different strands of a QlikView project, whether this is a super user, a data owner, or a reporting lead. Today the BI community comprises ten super users – one in each area of the business – who are responsible for being the ‘go-to’ people for all QlikView-related queries. All communication between the BI team and the business is typically channelled through these ten users. Similarly there are seven data owners responsible for the data domains within each business area and nine reporting leads who work closely with the BI team during the report development process. The BI team also runs a monthly QlikView café. This is primarily a drop-in session for business users that provides an opportunity for users to speak with the BI team and understand more about how to drive value from the tool and what is potentially coming up in future application releases. Governance National Express maintains a flexible approach to governance within its BI community. Master data is managed through the data owners, for example, whereas demand for new applications and enhancements is rationalised and prioritised through the BI reporting leads in conjunction with the executive management team. This process ensures that deliverables are prioritised based on the value they bring to the business whilst also ensuring there is no duplication of effort or requirements across departments. Equally, BI super users and existing QlikView users act as the contact points for all information queries ensuring that the QlikView tool is utilised as much as possible and the company can maximise the return on its investment. © MWD Advisors 2014
Analytics case study: National Express 7
Technology and infrastructure
The QlikView environment takes direct feeds from the company’s data warehouse which is housed
on SQL Server, as well as taking feeds from other operational and legacy data sources. The data
warehouse is managed by a third party who also provides the ETL layer for extracting and loading
data into the QlikView environment using SQL Server Integration Services.
Predictive analytics is currently supported through SAS and Excel to forecast year-on-year business
performance, for example. This is a relatively manual process at the moment and involves bringing all
the data together in one place (some of it is held in Excel spreadsheets) so the eventual aim is to port
this information to QlikView and build a reporting app around it.
National Express also uses Google Analytics for web analytics. The company reports on information
such as pick up rates, conversion rates on each route and why some are higher or lower, as well as
what people are searching for on the www.NationalExpress.com site.
The company’s CRM system holds information about customer churn and retention rates and the
number of journeys per passenger, as this information helps feed into customer retention efforts. The
end game, as mentioned previously, is to have a revamped CRM system that is built around a single
customer view which will feed QlikView directly, as well as the data warehouse.
The results
Nine months after the first QlikView application was released, National Express’ BI project has been
deemed a big success delivering in the region of six-figure revenue benefits for the company. The
ability to access more data within a self-service BI environment and the addition of new reporting
applications has brought many business benefits, including:
The ability to access and analyse competitor intelligence and market pricing data to assess
National Express’ value for money.
Improved customer service and value through the analysis of sales compared with routes (via
Google maps) has helped deliver network and route efficiency.
Time savings in report production. Network planning was historically a manually-driven
process; with QlikView, users can now look at route performance, drill down into detail and
make optimal route suggestions, saving the team lots of time.
By changing to a self-service BI environment National Express has been able to release
development time from the BI team, allowing them to work on more customer-focused
reporting apps.
Forecast compliance is now within 0.5%, and although this is not entirely attributable to
QlikView, having access to timely data and the analysis tools has helped make this possible.
The ability to analyse loads, routes, carriers, tendering, bookings, customs filings and payment
on a by-order basis has enabled National Express to reduce cost variables.
By tracking supplier performance against service level agreements the company has been able
to identify opportunities, negotiate intelligently, and tier contracts based on its visibility into
performance.
Similarly, part of the process of measuring success comes in the form of a monthly BI scorecard which
is distributed by the BI team to the executive board and all super users. The scorecard targets the
team against particular KPIs such as the percentage of total reports rationalised and migrated to
QlikView, as well as the number of new reports developed. In addition to this the team performs a
monthly user survey to assess whether the BI team is deemed to be performing in the context of the
overall business plan.
© MWD Advisors 2014Analytics case study: National Express 8
Recommendations for BI adopters
In our conversations with Helen Blaikie, Head of Business Planning at National Express, she offered
many recommendations for organisations embarking on a similar initiative. The overall essence of her
advice centred on having the right approach and processes in place to successfully engage people and
manage stakeholder expectations. There are a number of methods and tactics employed by National
Express to achieve this aim, some of which are outlined below:
Engage your most senior managers from day one. The BI team focused on selling the
vision of how the company needed to shift from purely using data to run the business, to
using information to drive competitive advantage. This involved clearly articulating its BI
strategy to the executive board, the steps involved in delivering on this strategy and how it
aligned with the overall corporate strategy. As a result the BI team was able to secure
commitment and resource from the top.
Outline what the benefits will be for each of the key stakeholders involved. The BI
team wasn’t content with just securing senior management buy-in; their communication plan
extended to the heads of business units to ensure they understood the vision and how it
would directly benefit them.
Consider delivering BI functionality and information that the business hasn’t had
before. National Express was keen to learn from the mistakes of a previous BI project
which failed, and so choose to make their initial BI application something the business
needed, but hadn’t had before. Its successful rollout not only delivered net new value to the
business but also helped drive additional momentum and buy-in.
Build adoption momentum at the top. By giving its Managing Director access to the
first BI application, the BI team was able to let him experience for himself the value and
benefits of having access to new data and reports. This had the knock-on effect of generating
more buzz and awareness amongst senior managers about the BI rollout.
View technology as only a small part of the overall project. National Express found
the most significant effort for the BI team was securing buy-in. Sourcing, developing and
implementing BI technology proved to be a relatively small proportion of the overall
endeavour.
Build a BI environment and community around your early successes. By assigning
different community roles such as super users and data owners early on and by promoting
usage via the QlikView café, National Express has been able to gain further buy-in and
momentum behind the project.
© MWD Advisors 2014Analytics case study: National Express 9 Best practice insights National Express’ BI initiative demonstrates a number of important best practices to apply when implementing a self-service BI practice. The first of these is that the initiative was aligned to some clear corporate goals and objectives. By pairing its BI strategy to the company’s vision and core values and the resulting objectives and KPIs used to measure performance, National Express was able to promote a common understanding of the scope and purpose of its BI project and ultimately ensure it received the appropriate buy-in and support. An important part of this process was the role of the company’s Managing Director. By ensuring he was on board with the initiative’s aims and objectives early on, and was trained and actively used the first BI application, the BI team was able to use this senior level validation to promote user acceptance and amplify its value and benefits to the broader business community. On a similar note, another key factor in National Express’ success was the support it put in place around stakeholder engagement and management. From day one the BI team actively sought to identify the key stakeholders for the project and make sure they understood the potential value the BI initiative would bring to their area of the business. Again, this helped secure ongoing commitment and support; furthermore the increased level of interest and the subsequent uptick in demand helped the BI team secure the additional resource needed to grow and expand its BI capabilities and hence drive more value out of their BI investment. Finally, a large part of the success of National Express’ BI story can be attributed to its active BI community. Part of this work has involved assigning roles and responsibilities, such as super user and reporting lead, to certain individuals within the business, which in turn helped National Express create a community of practice that drives the message around BI and its purpose and benefits. At the same time this organisational structure has helped improve collaboration and participation between the BI team and the business. This is particularly evident during user acceptance testing and as part of the change request process as ideas, issues and resolutions are fed back and communicated on a continual basis. This improved level of responsiveness and communication has meant changes are being turned around on a much quicker basis which, not surprisingly, is seen as a huge benefit and potential cost saving for the business. © MWD Advisors 2014
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