. Report Reducing order fallouts: Key to success with business services January 2015 Mark Mortensen and Anil Rao
Reducing order fallouts: Key to success with business services i Contents 1 Executive summary 2 2 Customer service is the most important aspect of the customer experience 3 3 B2B order fallouts impact customer experience and increase time and cost of the lead-to-cash cycle 4 4 Poor order quality is the top reason for order fallouts 5 5 Comptel s Service Order Validator enables CSPs to improve order quality and reduce order fallouts 7 6 Summary 8 About the authors 9 About Analysys Mason 10 Research from Analysys Mason 11 Consulting from Analysys Mason 12 List of figures Figure 1.1: Order fallout improvement curve [Source: Analysys Mason, 2015]... 2 Figure 2.1: Customer lifecycle [Source: Analysys Mason, 2014]... 3 Figure 2.2: The five components of customer satisfaction that can be changed by a CSP and the relative leverage on customer satisfaction [Source: Analysys Mason, 2014]... 4 Figure 3.1: Flow through provisioning [Source: Analysys Mason, 2015]... 4 Figure 3.2: Increasing cost of order fallouts [Source: Analysys Mason, 2015]... 5 Figure 4.1: Relationship between service complexity and order fallouts [Source: Analysys Mason, 2015]... 5 Figure 4.2: Evolution of service fallout for a high-volume, low-complexity service [Source: Analysys Mason, 2015]... 6 Analysys Mason Limited 2015 Contents
Fraction of failed orders (%) 2 1 Executive summary The needs of business customers have always been a primary concern for communications service providers (CSPs) because of the significant revenue potential. Enterprise business services contribute a considerable portion of revenue and, in some cases, represent as high as about a third of Tier 1 CSPs revenue. In the rapidly changing business environment and the growing maturity of the digital economy, the focus on business services will increase several folds, with the promise to become a key pillar for new revenue growth. To succeed in the enterprise business services segment, CSPs must focus on improving the customer experience, in all phases of the customer lifecycle. Order fallouts have been a perennial problem for CSPs; they stretch the lead-to-cash cycle time, increase operational costs and result in a poor customer experience. Analysys Mason research shows that about 35% of orders fail during the initial six months of a new service launch, with poor order quality being the primary reason, contributing to about 20% of failed orders. 40 35 30 Figure 1.1: Order fallout improvement curve [Source: Analysys Mason, 2015] 25 20 15 10 5 0 6 12 18 24 30 36 Time (months) Improving order fallout rate is a journey that depends on various factors including the complexity of the service, the existing order management capabilities and the willingness of CSPs to invest in next-generation order validation tools. By implementing the latest order management functions and applying advanced validation techniques early in the order capture process, CSPs can reduce the amount of order fallouts and improve the customer experience. Comptel has partnered with Salesforce and CloudSense to launch a hybrid, cloud-based, end-to-end order management solution. Comptel s Service Order Validator application works seamlessly with Salesforce CRM and CloudSense Configurator CPQ modules in the cloud, and integrates into its own on-premise order management and fulfillment solution. Analysys Mason Limited 2015 Executive summary
3 2 Customer service is the most important aspect of the customer experience CSPs operate in a hyper-competitive business environment where market differentiation is increasingly based on delivering a superior customer experience, particularly via customer service. Customer service includes all of the operations touch-points that a customer has with a CSP during his/her lifecycle. These include: Evaluate: Online and Customer Service Representative (CSR) interaction accessibility and quality Join: Order processing and provisioning On-boarding: Service setup, payment and training Support: Call centre, web support and self-care Renew: Proactive contact, confirm and promotion of relevant new offers Figure 2.1: Customer lifecycle [Source: Analysys Mason, 2014] Each step involves different interactions with the employees, systems and processes required to either satisfy or impress the customer. According to surveys conducted by Analysys Mason, customer service directly related to the operations that support the service, making up approximately one-third of the customer satisfaction score, while reliability represented one-quarter (Figure 2.2). The Join and On-boarding phases are applicable to this whitepaper. Analysys Mason Limited 2015 Customer service is the most important aspect of the customer experience
4 Figure 2.2: The five components of customer satisfaction that can be changed by a CSP and the relative leverage on customer satisfaction [Source: Analysys Mason, 2014] Poor customer service negatively impacts customer experience, causing customers to churn to competitors. Operators pay a hefty price for churn; acquiring new customers can be up to three to four times more expensive than retaining existing customers. This is much more pronounced in the B2B services space because of the high revenue potential. 3 B2B order fallouts impact customer experience and increase time and cost of the lead-to-cash cycle In the context of a B2B customer lifecycle, operators should pay particular attention to the Join and Onboarding phases. Flow-through provisioning and automation can help to some extent, but order fallouts can be expensive, leading to high on-boarding costs and a prolonged lead-to-cash cycle. In the worst case scenario, despite all efforts by the operator to rectify the order via the resolution processes, the customer may still decide to cancel the order, either because the delay is unacceptable or they just decided to take their business to a competitor. Figure 3.1: Flow through provisioning [Source: Analysys Mason, 2015] In scenarios where the customer gets involved, the cost of servicing the order fallouts can be even more expensive because of the high labour costs associated with having highly skilled technical support and field support staff. The overall costs can shoot up further if the operator has to supply some replacement kit. Analysys Mason Limited 2015 B2B order fallouts impact customer experience and increase time and cost of the lead-to-cash cycle
5 Figure 3.2: Increasing cost of order fallouts [Source: Analysys Mason, 2015] For a Tier 1 CSP with about 10,000 order fallouts annually, failure to have the right systems and processes in place could result in a heavy financial cost, upto about USD 500,000 in this case. While the operator incurs mounting costs, the prolonged service delivery times causes customer frustration and a poor customer experience. 4 Poor order quality is the top reason for order fallouts The propensity of order fallouts is directly related to the service complexity and the newness of the service. For services that have been offered over a number of years (such as POTS), CSPs fully understand how to capture accurate orders, validate them, and design and deliver the services at a minimal cost. Today, one would consider POTS as a low complexity service, with order fallout of a negligible 2% to 3%. Medium complexity services such as Ethernet, private line and broadcast video that have existed for a few years would have a slightly higher fraction of order fallout, usually in the range of 12% to 15%. On the other hand, services such as IP VPN, unified communications and VLAN are a relatively new breed of telecommunication services. CSPs can expect about 25% of order fallouts for these extremely complex services. (Figure 4.1) Figure 4.1: Relationship between service complexity and order fallouts [Source: Analysys Mason, 2015] The impending evolution of telecommunications networks towards virtualisation, led by Network functions virtualisation (NFV) and Software defined networking (SDN) technologies, will introduce a new dimension of network complexity. The transition to a fully virtualised network environment will take at least seven to ten years; and during this period, CSPs will have to contend with the co-existence of both the legacy networks and Analysys Mason Limited 2015 Poor order quality is the top reason for order fallouts
Fraction of failed orders (%) 6 virtualised next-generation networks. Identifying and resolving failed orders in such a complex network environment can be an extremely time consuming exercise and can lead to increased costs. However, it is important to note that improving order fallout is always a journey and varies greatly. When CSPs plan to introduce new services, it is difficult to prepare for every failure scenario that could potentially occur. No matter how much planning and pre-testing is carried out, there may be cases where order fallouts will occur, and typically, 35% of orders fail during the initial six months of introducing a new service. Figure 4.2 depicts the order fallout trend of a high-volume, low-complexity enterprise service. As such, a number of factors can contribute to order fallouts, but key amongst them are: Poor order quality or ill-formed orders In-flight changes Poor inventory records False notion of can be serviced 40 35 30 25 20 In flight changes Can be serviced Poor inventory records Ill formed orders Figure 4.2: Evolution of service fallout for a highvolume, low-complexity service [Source: Analysys Mason, 2015] 15 10 5 0 6 12 18 24 30 36 Time (months) Ill-formed orders are the biggest contributor to order fallouts, which is usually around 20% in the initial months. In many cases, this is largely because of a significant gap between what can be delivered in reality and what the order capture systems think can be delivered. At the time of capturing the order, the order entry system usually relies on the standard boilerplate product definitions and doesn t take into consideration: the feasibility of delivering the service with the requested configuration, and up-to-date information on the availability of network and IT resources This type of order validation is typically carried out much later in the process, most often manually, because of the complexity of the service and the highly bespoke nature of the requirements, leading to a protracted order capture cycle, significant duplication of effort and rework, and a poor customer experience. Other circumstances can contribute to order fallouts and exacerbate the situation causing further delays and high costs. In-flight changes: The customer can request changes to the order that is in progress but has not yet reached the point of no return. The CSP would then need to repeat the order validation process for the changed requirements Analysys Mason Limited 2015 Poor order quality is the top reason for order fallouts
7 Poor inventory records: Order entry and validation processes heavily rely on accurate inventory. Incorrect representation of the inventory can lead to false positives or false negatives, causing the wrong allocation of resources and further aggravating the scale of the inventory data quality. False notion of can be served : Often times, CSPs don t have sufficient safeguards in their order capture systems to establish whether they are in a position to fulfil the service in a particular region or a country, or source specific equipment requested by the customer. By leaving these types of validations too late in the cycle, CSPs risk breaking the promises made to the customer at the time of initial engagement. Clearly, CSPs need to apply more robust order validation techniques, especially at a very early stage in the order capture process to minimise order fallouts and maximise efficiency. 5 Comptel s Service Order Validator enables CSPs to improve order quality and reduce order fallouts Cloud-based sales and order management systems are an attractive proposition for CSPs, enabling them to increase responsiveness and reduce costs. Companies such as Salesforce have achieved success providing a SaaS-based sales order capture and customer order management solution, enabling seamless handovers between sales and delivery teams throughout the lead-to-cash cycle, supporting efficient, automated processes and increasing delivery accuracy. By combining the benefits of a SaaS-based architecture with strong feasibility and validation processes based on both product and service catalogues, CSPs can reduce order fallouts and reduce the lead-to-cash cycle time. Comptel has joined forces with cloud-based solution providers, Salesforce and CloudSense, to launch a preintegrated order management solution that works seamlessly in a hybrid cloud environment. (Figure 5.1) Figure 5.1: Comptel s Service Order Validator application in the Salesforce cloud [Source: Comptel, 2015] Analysys Mason Limited 2015 Comptel s Service Order Validator enables CSPs to improve order quality and reduce order fallouts
8 Designed as an open platform, Salesforce has been leading the way in the cloud-based sales automation marketplace, and increasingly, more CSPs, especially those operating in the business services segment, are considering Salesforce CRM as their solution of choice. CloudSense is a native Salesforce application providing multi-channel sales and customer order management capabilities. The Configure, Price and Quote (CPQ) solution provides the commercial intelligence and the product catalogue functions, and is tightly integrated with the Salesforce CRM module. Comptel brings the service order management and service fulfillment capabilities to the solution and works seamlessly out of the box with CloudSense and the Salesforce open platform. At the heart of Comptel s solution is the Service Order Validator application that brings service awareness capability to the front-end processes such as lead and order creation. The solution improves order quality and reduces order fallouts by performing real-time, pre-order service design feasibility and validation - collaboratively managing the network service design and assign processes. Enabled by CloudSense s product catalogue and Comptel s service catalogue via Service Order Validator, CSPs can quickly modify commercial attributes of the order. Comptel Service Order Management provides the technical attributes for the order during the configuration, pricing and quoting processes in the CloudSense Configurator CPQ module. As a last step, the solution validates the technical feasibility and reserves resources during runtime, ensuring the quote can be fulfilled. 6 Summary B2B order fallouts can cost CSPs dearly, leading to poor customer experience, churn and high triage costs. As the evolution of network technologies towards virtualisation gains pace, more services are expected to be delivered over an NFV/SDN enabled networks. CSPs will find it extremely challenging to resolve failed orders in an increasingly complex network, with the dynamic, flexible and temporal nature of virtualised resources. Long resolution processes will be unacceptable. CSPs will need to consider more than the traditional operational processes while making investment decisions on either improving existing systems or implementing a new order management solution. Analysys Mason Limited 2015 Summary
1 9 About the authors Dr Mark H. Mortensen (Principal Analyst) is the lead analyst for Analysys Mason s Customer Care and Service Fulfilment research programmes, which are part of the Telecoms Software research stream. His recent interest areas include customer self-care, automation of fulfilment processes, and data and software architecture for agile, real-time systems. The first 20 years of Mark s career were spent at Bell Laboratories, where he distinguished himself by starting software products for new markets and network technologies and architecting the interaction of BSS/OSSs with the underlying network hardware. Mark was Chief Scientist of Management Systems at Bell Labs, and has also been president of his own OSS strategy consulting company, CMO at the inventory specialist Granite Systems, VP of Product Strategy at Telcordia Technologies, and SVP of Marketing at a network planning software vendor. Mark holds an MPhil and a PhD in physics from Yale University and has received two AT&T Architecture awards for innovative software solutions. He is also an adjunct professor at UMass Lowell in the Manning School of Management, specialising in business strategy. Anil Rao (Senior Analyst) is a member of Analysys Mason s Telecoms Software research team and is the lead analyst for the Service Assurance programme, focusing on producing market share, forecast and research collateral for the programme. He has published research on IP probes, real-time network analytics and the importance of service assurance in reducing churn and improving customer experience. He holds a BEng in Computer Science from the University of Mysore and an MBA from Lancaster University Management School, UK. 1 Published by Analysys Mason Limited Bush House North West Wing Aldwych London WC2B 4PJ UK Tel: +44 (0)20 7395 9000 Fax: +44 (0)20 7395 9001 Email: research@analysysmason.com www.analysysmason.com/research Registered in England No. 5177472 Analysys Mason Limited 2014 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher. Figures and projections contained in this report are based on publicly available information only and are produced by the Research Division of Analysys Mason Limited independently of any client-specific work within Analysys Mason Limited. The opinions expressed are those of the stated authors only. Analysys Mason Limited recognises that many terms appearing in this report are proprietary; all such trademarks are acknowledged and every effort has been made to indicate them by the normal UK publishing practice of capitalisation. However, the presence of a term, in whatever form, does not affect its legal status as a trademark. Analysys Mason Limited maintains that all reasonable care and skill have been used in the compilation of this publication. However, Analysys Mason Limited shall not be under any liability for loss or damage (including consequential loss) whatsoever or howsoever arising as a result of the use of this publication by the customer, his servants, agents or any third party. Analysys Mason Limited 2015 About the authors
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