Research Forecast Report
Analytics software solutions:
worldwide forecast 2014–2018
September 2014
Contents
5. Executive summary
6. Capsule summary: analytics software solutions worldwide forecast 2013–2018
7. The worldwide analytics software market is forecast to grow from USD2.1 billion in 2013 to USD3.8 billion in 2018, at a 12.9% CAGR
8. Revenue assurance systems revenue will continue to grow, but to a lesser extent than that of business analytics systems
9. Growth in analytics systems revenue will be highest in APAC, but NA will continue to generate the largest proportion of revenue
10. Mature markets will maintain their share of revenue during the forecast period, driven by increasingly sophisticated analytics systems
11. Recommendations
12. Recommendations for CSPs
13. Recommendations for vendors 14. Forecasts
15. Business analytics revenue will grow during the forecast period, driven by expanding analytics tools applications and geographical spread
16. CSPs in NA and Western Europe have invested heavily in analytics solutions and will continue to do so
17. EMEA and APAC will increase their share of business analytics
19. Spending growth will be highest in emerging markets the highest in the APAC and LATAM
20. Growth in revenue assurance systems revenue will be lowest in mature markets and highest in the emerging markets of APAC and LATAM 21. Market drivers and inhibitors
22. The requirement for CSPs to process growing volumes of data in real time will drive them to continue to deploy analytics tools
23. Lack of clear application-level business drivers could hinder the
predicted high level of growth in the analytics software solutions market
24. Analytics software solutions market drivers [1]
25. Analytics software solutions market drivers [2]
26. Analytics software solutions market drivers [3]
27. Analytics software solutions market inhibitors [1]
28. Analytics software solutions market inhibitors [2] 29. Business environment
30. The business environment in 2013
31. Regional outlook for 2014
32. Analytics innovation adoption 33. Market definition
Contents
36. Definitions of components in an analytics framework [1]
37. Definitions of components in an analytics framework [2]
38. Revenue assurance
39. Business analytics
40. Definition of geographical regions [1]
41. Definition of geographical regions [2]
42. Definition of geographical regions [3]
43. Key business drivers and market characteristics and how they map to different operational and software strategies
44. About the authors and Analysys Mason
45. About the authors
46. About Analysys Mason
47. Research from Analysys Mason
48. Consulting from Analysys Mason
List of figures
Figure 1: Analytics product innovations and market influencers by sub-segment
Figure 2: Analytics software solutions revenue 2013 and CAGR 2013– 2018, by region
Figure 3: Analytics software solutions revenue 2013 and CAGR 2013– 2018, by sub-segment
Figure 4: Analytics software solutions revenue, worldwide, 2013–2018 Figure 5: Analytics software solutions revenue by sub-segment, worldwide,
2013–2018
Figure 6: Analytics software solutions revenue by region, worldwide, 2013– 2018
Figure 7: Analytics software solutions revenue worldwide, by region, 2013 and 2018
Figure 8: Business analytics software solutions revenue, worldwide, 2013– 2018
Figure 9: Business analytics software solutions revenue by region, worldwide, 2013–2018
Figure 10: Business analytics software solutions revenue worldwide, by region, 2013 and 2018
Figure 11: Revenue assurance software solutions revenue, worldwide, 2013–2018
Figure 12: Revenue assurance software solutions revenue by region, worldwide, 2013–2018
Figure 13: Revenue assurance software solutions revenue worldwide, by region, 2013 and 2018
Figure 14: Drivers and enablers of growth in the analytics software solutions market during the forecast period
Figure 15a–c: Analytics software solutions market drivers Figure 16a–b: Analytics software solutions market inhibitors
Figure 17: The features of analytics software solutions and their position on the innovation adoption curve, worldwide, 2013
Figure 18: Analytics solutions market taxonomy Figure 19: The components of an analytics application Figure 20a–b: Definitions of analytics components
Figure 21: Definition of the revenue assurance sub-segment Figure 22: Definition of the business analytics sub-segment Figure 23a–c: Regional breakdown used in this report
Figure 24: Mapping of key business drivers and market characteristics according to business environment, and operational and software strategies
Mature markets will maintain their share of revenue during the forecast
period, driven by increasingly sophisticated analytics systems
The overall market share of revenue will not change significantly during the period. Each telecoms market is affected by different factors – the most significant is the level of market maturity.
NA is the largest user of analytics tools driven by market maturity and the need for innovative marketing to maintain market share. New technology such as software-defined networks will also drive uses of analytics to provide dynamic optimisation of network functions.
Revenue in LATAM will grow, but the region will lose out to other faster-growing regions, such as APAC, and will experience a decline in the overall market share.
Revenue in the EMEA region will grow, as CSPs in the mature markets of Western Europe invest in
more-sophisticated analytics tools to maintain market share and optimise network assets.
APAC’s share of revenue will grow the fastest, driven by underlying telecoms market growth of subscribers and
service revenue, a high level of innovation and roll-out of new services particularly LTE.
Figure 7: Analytics software solutions revenue worldwide, by region, 2013 and 2018 [Source: Analysys Mason, 2014]
40.7% 41.0% 5.7% 4.7% 36.7% 37.0% 16.9% 17.3% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 2013 2018 P e rc e n ta g e o f rev e n u e APAC EMEA LATAM NA
Recommendations for CSPs
Short term Have firm plans in place for a big data analytics strategy to ensure that a powerful data store and low-cost computing capability is available to all levels of the enterprise.
Adopt the principles outlined by the TM Forum’s Frameworx Information Framework (SID) to ensure a standardised approach to different data sources.
Adopt a set of standard products or language such as ‘R’ (also known as GNU S) to enable different teams to share common analytics data models.
Revenue assurance teams should work with a common data set to other analytics use cases to ensure a streamlined set of tools and resources.
Medium and longer term
Create a central organisation that is responsible for developing analytics models. This will provide a shared understanding across the enterprise and governance that a federated set of teams would find difficult to achieve.
Appoint a chief data officer who will take responsibility for all data sets and is the custodian of which data can be used legally. Use the analytics infrastructure in any customer experience management initiatives in order to compare internal KPIs with any
external surveys, such as the Net Promoter Score.
Executive summary
Recommendations
Forecasts
Market drivers and inhibitors
Business environment
Market definition
About the authors
Justin van der Lande (Principal Analyst) leads the Analytics Software Strategies, Customer Experience
Management Software Strategies and CSP IT Strategies research programmes, which are part of Analysys Mason’s
Telecoms Software research stream. He specialises in business intelligence and analytics tools, the functionality of which cuts across all of the research programmes in this area. He also provides project management for large-scale projects within our Telecoms Software research. Justin has more than 20 years’ experience in the communications industry in software development, marketing and research. He has held senior positions at NCR/AT&T, Micromuse (IBM), Granite Systems (Telcordia) and at the TM Forum. Justin holds a BSc in Management Science and
Computer Studies from the University of Wales.
Atul Arora (Analyst) is part of the Telecoms Software research team and contributes to the Analytics Software
Strategies, Customer Care and Digital Economy Software Strategies programmes. He joined Analysys Mason in
2013 after working as an intern analyst in the telecoms sector for a year. Atul has worked on a range of projects focused on telecoms verticals, cloud services and mobile services in emerging markets. He holds a bachelor's degree from Jaypee University (India) and a Master's degree from University College London.
About Analysys Mason
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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.
