Telecommunications and Data AnalyticsImproving financial performance by turning challenges into opportunities

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The telecommunications industry has experienced rapid changes over the past decade as a result of technological advancements, regulatory influences and increased competition.

Companies have responded to these changes with strategic acquisitions, multiple and complex pricing plans, and product bundling. They have also sought to offer differentiated products such as IPTV and cloud computing. These changes in the market present new challenges which could undermine earnings and impact key industry performance measures including EBITDA and Average Revenue Per User (ARPU).

The telecommunications industry regularly uses data analytics in fields such as customer analysis and network optimisation. For financial analyses such as identifying risks, which could negatively impact an entity’s financial performance, communications service providers have traditionally used statistical sampling techniques that cover only short time periods and a limited subset of data.

To better understand and respond to these risks, Chief Financial Officers (CFOs) can now use more sophisticated data analytic methods to supplement the audit advisory services they receive. In particular, a cost-effective opportunity exists to analyse large volumes of data over an extended period, providing more insight and greater agility to respond.

In this article, we discuss five areas in which data analytics can be used to address the opportunities and risks faced by communications service providers: ARPU leakage, network development, profitability of stores and franchises, phone inventory and cash outflows.

CFOs can now use more sophisticated data analytic methods to identify revenue opportunities and address risks that negatively impact their company’s margin

Data analytics and improving financial resultsThe following five cases show that the combination of deep industry insights and data analytics offer CFOs the unique ability to effectively address industry specific financial risks and create opportunities by analysing data over an extended period of time.

Time

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CFOs can make the adjustments they need to get ARPU back on the path to growth

Telecommunications companies invest heavily in capturing and analysing ARPU. In recent years, the number of variables which contribute to ARPU has increased alongside the complexity of product offerings, bundling and billing arrangements. As a result, CFOs may struggle to understand why ARPU is changing and what they can do to arrest downward trends.

Outperforming competitors requires a granular, in-depth understanding of the factors that drive changes in ARPU – data analytics make this possible at levels not previously achievable. Analytics can also identify outliers that provide meaningful clues to the sources of underages or overages. Armed with this information, CFOs can make strategic pricing decisions to get ARPU back on the path to growth.

Deloitte recently helped a leading Australian telecommunications provider understand the reasons behind changes in ARPU by analysing how customers moved between certain price plans. This exercise significantly helped the carrier optimise its strategic price setting.

1 ARPU leakage – identifying outliers

Price plan

AR

PU

Figure 1: ARPU analytics

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2 Network development – project accounting and capital expenditure tracking

As communications service providers invest significant time, effort and capital into optimising and expanding their networks, tracking and accounting for these projects is essential for CFOs and internal auditors. CFOs need to decide which

aspects of network building exercises are booked as expenses and which can be capitalised as assets. Conducting data analytics on capital works in progress can identify projects with unusual characteristics that present increased risks of capital loss.

By analysing variables such as actuals versus budget, timing of spend, and cost composition across all capital projects – week to week and month to month – CFOs can create a risk profile for each project. They can then pinpoint those projects which need additional management attention to minimise downside financial exposure.

CFOs can pinpoint those projects which need additional management attention to minimise downside financial exposure

Figure 2: Network development – detailed project risk profile

Risk Score

Proj

ect

turn

over

(YTD

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Projects that fall within the accepted turnover/risk ratio

Projects with increased risk that warrant further investigation

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3 Profitability of stores and franchisees

Many customers buy telecommunication services, phones and related devices through company-owned or franchised retail stores. Data analytics gives CFOs the opportunity to measure the performance of each store using more granular metrics than profitability alone. This extends to unobvious correlations not historically visible.

For example, management can review the controls and processes at stores that significantly outperform or underperform relative to their peers and potential catchment. CFOs can ensure they are comparing like for like, by taking into account factors such as the particular demographics for each store location along with store size and operating attributes.

This can provide valuable insights for future planning. In addition, CFOs can identify the stores at greatest risk of poor financial performance and take appropriate action.

Catchment spend on communication devices

High performing stores

Stores with operational improvement opportunities

Underperforming stores to consider for closure and / or relocation

Stor

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CFOs can identify stores at greatest risk of poor financial performance and take appropriate action

Figure 3: Store performance

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4 Phone inventory – minimizing holding costs

Mainly as a result of the introduction of the smart phone, phone inventory has significantly increased in value and now represents a substantial cost to operators. As a consequence, adequate monitoring of phone inventory levels has become important in order to minimize holding costs and prevent the organisation from unnecessary losses relating to impairment of outdated phone inventory.

Traditional inventory management systems provide high level insight into the aforementioned, however, typically allow only a retrospective view on the inventory challenge. CFO’s can use data analytics to perform an in-depth analysis of its existing phone inventory, analyse product margins at the lowest level and predict phone inventory with an increased risk of becoming obsolete. This will help improve stock replenishment, optimise phone inventory levels and reduce costs relating to holding inventory.

CFO’s can improve stock replenishment, optimize phone inventory levels and reduce costs relating to holding inventory

Average number of days to sell

Figure 4: Optimising inventory levels

Inve

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Communication devices above optimal inventory levels

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5 Cash outflows

Communications service providers typically experience significant cash outflows when purchasing fixed assets such as network components and communication devices. This warrants increased scrutiny of a telco’s payments processing and control. CFOs can use data analytics to validate

existing supplier databases and identify any invalid or unused suppliers. They can also verify that purchase authorisations comply with internal authorisation rules, including instances of duplicate payments (which occur more frequently than many realise). As a result, CFOs can gain insights into breaches of purchase authorisation procedures and take steps to reduce unnecessary loss.

Deloitte helped a prominent Australian telecommunications carrier conduct an in-depth analysis of the effectiveness of its payments function. Several ideas to improve processes and controls were implemented.

ConclusionGiven the massive number of transactions processed by telecommunications companies; and the costs and complexity involved in their operations, data analytics offers CFOs a valuable opportunity for enhancing the frameworks and procedures they adopt to drive profitability and minimise unnecessary downside risk.

CFOs can gain insights into breaches of purchase authorisation procedures and take steps to reduce unnecessary loss

About Deloitte AustraliaDeloitte’s next-generation advisory services combine deep telecommunication industry expertise with leading-edge financial data analytics. Our advisory professionals can draw on the expertise of more than 100 data analytics experts across Australia. We can help CFOs accurately pinpoint the challenges and risks they face, correctly interpret the results of data analytics exercises and maximise the benefits that result. Please contact us for more information about this topic or the role data analytics could play in your organisation.

Please visit www.deloitte.com/au/tmtinsights for more Deloitte thought leadership on issues and opportunities in the Telecommunications sector.

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About the authors

Philip Takken is a Director in Deloitte’s Technology, Media and Telecommunications practice in Sydney. In the last fourteen years Philip has been providing Assurance and Advisory services to major incumbents as well as emerging telecommunication companies in both the USA and Asia Pacific. Tel: +61 2 9322 3957 Email: phtakken@deloitte.com.au.

Slav Tabachnik is a Director in Deloitte’s Data Analytics practice in Sydney. Slav has more than twelve years experience developing computer models to assist customer management, compliance, revenue and cost management activities using electronic data sets. Slav has applied these skills across a number of engagements in the telecommunications industry in Germany, Canada and Australia. Tel: +61 2 9322 7345 Email: stabachnik@deloitte.com.au.