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Tag Archives: Analytics

Addressing the Trust Gap. It is Possible

Analytics, Telecom Insights & Analytics

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In our previous blog, we spoke about how in today’s world of rapid and constant change it has become ever so important to make the most of real-time inflow of data. Data is the new oil – and like oil, data needs a refinery before it is used across business use cases. To quickly take a step back, this trend always reminds me of the comic Tintin and The Land of Black Gold – “Boom! … One day your car goes Boom!”. The plot revolves around car engines exploding because of faulty petrol at its source. Similarly, if data is not clean at the source, your business decisions are bound to go “BOOM”!

‘TinTin: Land of Black Gold’ by Hergé

 

Analytics has been commoditized today, with the entry of open source tools and technologies. However, there is a significant trust gap when it comes to the consumption of analytics. How much do you trust your data? How significant is the output of analytics in the organisations board meeting? While in our last blog we looked deeply into the trust gap and its roots, at the end of the day, we need to realise that analytics is just an application of Math-Technology-Business on data. So, if we believe in Mathematics, have faith in the technological revolution and are confident of our business intuition, there is no reason for analytics not to be considered as the most critical function – all that remains is refining the oil, i.e., data.

We at Subex, recognize and respect this trust gap. We also believe an analytics strategy should build around the golden triangle – People, Process, and Technology.  The first and most critical step would be to have analytics done in a democratized manner. Everyone in the organization, from the C-Level, to the Department Head level, to the Analyst level should be armed to be data-driven. The involvement of machine should not undermine the trustworthiness, nor should it lead to a decrease in human involvement; instead, you should leverage the best of both human and machine intelligence to improve products, enhance the quality of service (QoS) and derive more returns from your investments.

Does Human Intelligence + Machine Intelligence = Trust?

Taking the Human Intelligence + Machine Intelligence philosophy into account, we have come up with a concept known as Subex ACT (Analytics Centre of Trust), designed to bridge the Trust gap by covering the end-end cycle of Data-Insights-Decisions (D.I.D.). Let us take a quick look at the three pillars of our ACT program:

  1. Defining a Strategy

Before starting the analytics journey, it is imperative to assess the following

  1. What is the analytical maturity of the organization?
  2. What are my objectives from the analytical program vis-à-vis the business vision
  3. Do I have a roadmap in place?

The main Objectives of this process are:

  • Setting up the goals for the organization: The Strategy can help deliver competitive advantage, create incremental revenue opportunities, and reduce costs.
  • Assessing your analytics maturity vis-à-vis your goals: Understand where you are in terms of your analytics maturity and identify the target maturity which will help you reach the goals defined in step 1
  • Plan for the Transition: Understand how you will transition from your current maturity level to the desired maturity level and ensure the process is time-bound, tangible and step-wise. What we recommend is that you identify tangible use cases, such as churn, and move the analytics maturity of addressing churn from, say, 3 to 4. Once that is completed, define another use case and increase the maturity to address that similarly
  1. Setting up an Information Infrastructure

Post defining the analytical strategy it is imperative we have the right set of tools to handle the task at hand. The tools which organisations need today need to be the following:

  • Agile: Create the ability to address the problem statements based on the requirements
  • Scalable: Should be able to handle massive volumes and different types of data
  • Reliable: The information that is generated by the system needs to be trustworthy
  • Real-Time: For quick and accurate decision making the reports should be in real-time
  • API Integration: The tools should be compatible with API-based integration
  • User-friendly: Consumption of the reports/data should be easy to use
  • Secure: The tool should be compliant with security guidelines
  • Self-Serviceable: Accessible UI enabling the end user to self-generate reports

Such an Information Infrastructure should offer a self-service reporting environment wherein each stakeholder gets the access to the tools to analyze and act upon the information. This will not only reduce the time gap in execution but raise the operational efficiency to a new level. As the model evolves into an Analytics Centre of Trust (ACT), the transformation journey becomes smooth.

  • Analytical Driven Business Outcomes

The final piece of the Analytical Framework, is clearly towards the analytical output. For too long, organisations have set up analytics practices with a mandate towards delivering on analytics outcomes. Subex is of the firm belief that the key to analytics is to attain business outcomes while ensuring insights are available across all audience levels in a democratized fashion which is easily understandable.

Conclusion

The world of digital technologies is open for Telcos to build new business opportunities as well as excel on the existing ones. It’s time to identify the gaps in your analytics strategy and develop an ACT that helps you climb the ladder faster. As an organization is preparing to capture the active markets, your analytics goals must focus on using information as a strategic asset to generate revenue, improve operational efficiency and provide best-in-class customer service.

In our next blog, we will cover how Subex ACT helps CSPs regarding addressing these three pillars and how it helps bring Agility, an Analytics to Business mindset and Democratization through Consumable Outcomes to your organisation.

This blog has been co-authored with Sandeep Banga. 

The Analytics Trust Gap. It Is Very Real

Analytics

So, you are looking to start an Analytics Program within your organisation. You have the tools ready, you have the resources designated for the task, and you have all the required process you need in place to run a robust Analytics program. You expect to see a massive revenue growth within a year; however, after the passage of 365 days, the outcomes are well short of your expectations. At this point, you have a set of questions to ask yourself:

  • Where could I have gone wrong?
  • My organisation has a massive volume of data. Was the quality of my data not up to mark?
  • I had all the tools in place, with Artificial Intelligence automating all the processes. Where did I fall short?
  • I have received data from multiple sources? Is this causing the shortfall?
  • Have I ensured that the data residing in my data lakes are free from breaches and attacks?

All these questions which arise could ultimately lead you to lose faith in your analytics program.

Over the past several years, we have seen how data analytics has evolved from the simple exploratory level to the current predictive level. With Business Intelligence (BI) playing the pivotal role in decision making, organizations are seeking the power of advanced analytics and machine intelligence to attain agility and competitive differentiation. Telcos, which own the most significant share of customer data among all the industries, are in the best position to leverage them to achieve higher levels of maturity. However, a recent KPMG report reveals a paradox that despite the huge investments in data analytics, organizations are not able to build value around it due to lack of trust. According to the report, only 35% of decision-makers have a high level of trust in their own organization’s analytics, and 25% admit that they either have limited trust or active distrust in their analytics. Moreover, only 10% said they excel in managing the quality of data and analytics, and 13% said they excel in the privacy and ethical use of data and analytics

What Causes the Trust Gap?

The above findings come as no surprise considering the growing complexity associated with handling the data originating from disparate sources. Many studies now indicate that the once 4 Vs to describe key aspects of data (Volume, Velocity, Variety, and Velocity) has now grown to 10 (to include Variability, Veracity, Validity, Vulnerability, Volatility, and Visualization).

But besides the growing complexity of data, there are multiple other aspects which are leading to the trust gap, some of which are captured below.

Quality- a top concern

As the data grows more complex, analysis can be challenging. Poor data quality or incompetent analysis can lead to disaster. As Gartner puts it, “As organizations accelerate their digital business efforts, poor data quality is a major contributor to a crisis in information trust and business value, negatively impacting financial performance.”

Working with false or incomplete data could result in uninformed and biased decisions, which could prove harmful to the overall business. Gartner has also estimated that poor data quality can lead to an average of $15 million per year in losses.

Can we trust machines?

In today’s machine-controlled analytics landscape, building trust becomes even more challenging. The advent of artificial intelligence (AI), coupled with the advancements in machine learning (ML), has opened a plethora of opportunities in data analytics. We have seen many horror stories wherein placing complete faith in AI without human intervention has had disastrous consequences.

Integration of disparate data

Considering that organisations do not have a single source of truth when it comes to the data they gather, data integration is another major roadblock, resulting in poor execution and sometimes complete failure of analytics implementation. Organizations which are slow in their transformation journey confront challenges in integrating data of different formats. They lack the skills, training, and tools to build a centralized access and control policy. Historically, the self-service concept is appealing but has often fallen short of expectations due to barriers faced at multiple levels – technology, people, and process.

Security-an everlasting concern

There is no respite from data breaches and misuse. The fact that fraudsters are making headway by exploiting advanced techniques escalates the concerns.  The thin line between the security breach and the reputation of an organization brings the transformation to a halt.

These are but a few reasons to why a trust gap is being created, but they are very real. Should it remain, the trust gap will lead to severe implications in terms of competitive advantage, operational efficiency, and growth. The inability to rise as a data-driven organization means that they also lag mature organizations considering data-driven organisations witness 23x Customer Acquisition, 6x Customer Retention, and 19x Better Profitability (according to McKinsey). And non-data driven companies miss out on all these benefits.

It is clear – The time has now come to bridge the trust gap! The only question that now remains is, how? Stay tuned to our blog for the answer.

Actionable predictive analytics: overcoming the analysis paralysis

Analytics, Capacity Management, Network Capacity, Network Management

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Why standard forecasting analytics models fail to deliver in today’s world of complex digital networks and why telcos need a domain-specific analytics solution.

“Your analytical dashboards and visualizations look good, but I prefer actionable reports and insights”, said the deputy CEO of a Southeast Asia-based telecom service provider during one of our meetings last year. This was not just one odd instance. We have heard this many times in the past year from other CSP executives. There are many domain-agnostic AI/ML based analytics solution providers in the market, but what telcos really want is an analytical solution which provides end-to-end domain-specific actionable insights. Forecasting traffic or pointing out anomalies is one thing, but how to incorporate those recommendations into capacity planning? What is the root-cause for that anomaly so that it could be prevented in future? Instead of getting lost in analysis paralysis amidst thousands of fancy statistical metrics; a simpler, actionable and reliable predictive analytics solution is the need of the hour.

With the right mix of domain knowledge and analytics advantage, centered around the actual requirements of the network planners; Subex has come up with the concept of actionable predictive analytics. Network planners should be enabled for efficient, reliable and cost-effective capacity planning. Hence, here the focus is more on what matters to the telco network teams, i.e. the business values such as capex optimization, network performance improvement, customer experience enhancement and operational efficiency; rather than on underlying analytical components such as configured models or feature engineering.

Here are two of the most important aspects about Subex’s approach to predictive analytics which are different from the traditional forecasting models –

Multi-variate analysis

Unlike the traditional forecasting systems which predict the future trends for a metric based on the historical pattern of that given metric, in multivariate approach, the system understands the lagging or leading effect on the given KPI from other KPIs. With this, the telco can predict, in near real-time, what is going to happen in the future and adopt appropriate measures to prevent capacity issues. A multi-variate, self-learning forecasting model which runs on the in-house machine learning platform is complemented by domain-specific configurations and expertise which is equally essential for intelligent forecasting.

The figures below compare a multivariate model scenario that considers the lagging effect of KPI1 (e.g. customer complaints) on KPI2 (e.g. capacity utilization) with that of a traditional model that does not give such insights. In the first case, the operator does not get accurate results as yielded in the second case because there is a direct relation between traffic and customer complaints. For example, if there was an aberrant increase in traffic, the operator can take that fact into consideration for accurate prediction of future customer complaints.

One more use-case could be accurately predicting the time to capacity exhaust for a site if one of the neighboring sites is planned for decommissioning soon. In this case, with the help of geo-spatial analytics, the additional load on the given site due to decommissioning of the neighboring site would also be considered for calculating time to capacity exhaust.

capacity exhaust

Domain Specific Insights

Be it wireless or hybrid fiber-coaxial networks, even an accurate capacity forecast is incomplete without the required domain-specific insights. Without a proper root cause analysis for a network element exhausting soon (in terms of capacity), the network planners won’t be able to make the right decision about its proactive mitigation.

These are some questions to consider when developing your network augment action plan:

  • How many customers will be impacted when a given network element hits a capacity exhaustion threshold?
  • Will prioritizing the given candidate for capacity augment above other options result in the best customer experience improvement and maximized ROI?
  • What is the reason for this capacity exhaust? Is it because of seasonality, periodicity or cyclicity? Is it an anomaly due to some one-off event?
  • Will new Capex be required to address the capacity bottleneck, or are there alternatives to new spending?

Some of the insights that could be useful for the planners leveraging predictive analytics for capacity planning and management are shown below –

capacity planning

Predictive Analytics

Apart from the above two key differentiators, some other important aspects for a pragmatic, accurate and reliable predictive analytics solution are scalability and flexibility.

Multi-variate forecast models need to run thousands of simulations across the network to identify the correct correlated metrics for accurate predictions.  Such models need to be configurable, flexible and easy-to-understand for non-data scientists.

Are Traditional Data Warehouse Challenges Affecting Your Business?

Analytics

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With data emerging as the new currency for businesses, data warehousing demands a new approach in dealing with the challenges. As Gartner puts it, poor data warehousing practices “undermine the organization’s digital initiatives, weaken their competitive standing and sow customer distrust.” Telecom operators are among the most affected by data warehousing challenges as they handle billions of customer data generated from multiple sources like files and probes (SS7, SIP, SIGTRAN), as well as the massive volume of data streamed from social media platforms.

As the volume, velocity, variety, and veracity of data generated continue to grow; the traditional data warehouse approach flounders while managing and analyzing the data. With conventional data warehouse analytics offerings, answering even seemingly simple questions such as “Who are my ten best customers?” could take up to 5-10 days. Even after the team figures out the right criteria, compiling and analyzing the data could again be a time-consuming process. As the questions grow complex, the burden only grows further.

While in-memory databases have helped alleviate the problem to some extent by providing better performance but with rigid data models, it makes data analytics workloads more and more compute-bound. Even it is well understood that traditional data warehouse approaches have become arduous due to the IT dependency and upfront data modeling. As a result, the time to value grows longer, and the outcome materializes only when the business can start to use the reports and insights provided by the data warehouse. Since this approach is rigid, it may also call for data modeling changes, which will further delay the process execution.

Working with data always carried an inherent risk that false or incomplete data could lead to uninformed or even misinformed decisions. Telcos have a winning edge as they are the custodian of largest repository of customer data in the world. Therefore, businesses can no longer ignore these challenges as new business opportunities are emerging around data usage. Look at the sheer size of the data generated during a typical business day, an operator serving 80 million mobile subscribers generates around 20 billion Detail Records (xCDRs) daily.

Worldwide several Telcos have identified opportunities around data monetization – both internal and external. The growth of the Internet of Things (IoT), artificial intelligence (AI) and machine learning (ML) has largely contributed to this upswing. Telcos’ growing engagement with content providers, IoT companies, VAS companies and others prove they are striking it right. At this juncture, it becomes crucial for telecom companies to revise their data strategy around modern big data analytics tools.

Working with poor-quality data can also bring damage to the existing business, especially concerning customer value. As you know, customer preferences are evolving, so ensuring customer satisfaction and loyalty mostly relies on how quickly you address their issues. Big data and real-time analytics gain relevance in this context.

Hence, a robust big data platform is no more a luxury but a business imperative! Stay tuned to know more about Subex’s approach in handling the complexities around a traditional DWH and data quality issues.

For more information on how Subex is helping Telcos address gaps in their analytics approach through an end-to-end framework, attend a webinar we are hosting with Telecoms.com entitled, Bridging the Analytics ‘Trust Gap’ Within Telcos.

Register yourself here: http://bit.ly/2NzFXJF

The Trifecta Effect for Telco Analytics –Anomaly Detection

Analytics, General, Telecom Insights & Analytics

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Subex recently participated in the Monetising Big Data in Telecoms World Summit 2018, Singapore, where we demonstrated our expertise of 25+ years in the Telecom domain handling data at a massive scale. We did this by presenting on the topic: The Trifecta Effect for Telco Analytics –Anomaly Detection

To take a step back, Subex has partnered with 250+ telcos across 100 countries. We have been handling big data and have an understanding of the business of telcos working in different contexts, demographics and geographies, and at different stages of their growth. We have been leveraging analytics for 10+ years in the assurance portfolio, and have made a foray into analytics across all domains in the telecom sector. While starting on this journey, we did a survey across many operators and what came out was unexpected albeit not exactly surprising, based on our experience.

We saw that, while the telecom domain today is at the forefront of innovation, the industry can be considered as a relative laggard in adopting analytics, when compared with other industries. Around 60-70% of the executives still lack relevant data for decision making. To top it all, where analytics is being used, around 60% of the organizations are still not very confident about their analytics insights.

Based on our market research and after multiple interviews we believe that the reason for these above problems can be classified along the following categories:

  1. Poor ROI
  2. Multiple and Complex Dashboards
  3. Long Development Cycles
  4. Data quality issues
  5. Short Supply of Data Scientists
  6. Lack of Agility

To cater to these problems, we at Subex have designed a way to address these issues. Our solution, ROC Insights stands on three pillars which we call the Trifecta of Analytics: Agility, Cost & Consumption. Subex does this by

  • Delivering insights in less than 8 weeks
  • Following a pure OPEX model which takes care of the cost
  • Most importantly ROC Insights simplifies consumption of analytics insights tremendously through the use of storyboards

At the Monetising Big Data in Telecoms World Summit 2018, we explain how the Trifecta can be leveraged by using a simple example of Anomaly Analytics. For a telecom, with massive volumes of data, it is more difficult to detect anomalies in data than finding a needle in a haystack. In case of the latter we know that we are looking for a needle. In this case, we don’t even know what exactly one is looking for. However, it is extremely important for a telco to manage anomalies to mitigate risk and to prevent missing out on opportunities.

There is a very fine line between the definition of an anomaly and outlier. Rather the distinction is rather fuzzy as anomalies and outliers are intersecting but certainly not subsets. Take for instance, a queen bee in a bee hive. She is an outlier but not an anomaly. Anomalies usually remain undetected. They are unknown problems with unknown solutions. Our work detects, curates and qualifies these problems to move it from the unknown-unknown realm to the known-known realm by breaking it into parts, analyzing them using various ML/DL algorithms and as well doing causal analysis to find the root factors.

We talk of two examples where we work with Telcos to solve their anomaly problems using advanced analytics. In the first case, our solution of anomaly detection required modification as the client was based out of East Africa with pockets of high population density in vast open areas. We developed anomaly for cell sites using algorithms such as time series, manifold learning, LSTM etc. We did anomaly detection for different KPIs such as call duration, data and customer latching. This was further qualified along the dimensions of 2G/3G/4G, on-net/offnet and so on. Anomaly analysis generally suffers from the problem of ‘too many’ and difficulty in prioritization. Our solution gives revenue numbers to the anomaly and prioritizes them. Most importantly it looks also at the long term business impact of high value customers, churn etc. and also considers the factors whether load balancing is done by nearby cell sites and the customers were really impacted or not.

Our second use case was regarding our work for a client based out of N. America. They were having difficulty in detecting lost handset on time. This was causing them huge monetary loses. With the help of algorithms like probabilistic graphical model, Markov chain etc. we created algorithm to detect whether a handset was stolen or not. Our algorithm helped in improving the client’s solution 9 times in detecting the algorithm. As well in 80% of the cases, the instances were detected within 24 hours, thereby improving the customer’s bottom line.

All in all, the presentation provided for a good opportunity for attendees to understand how Subex is working with big data, and how ROC Insights can help telcos by pinpointing upon a very specific problem. At large, we enjoyed presenting at the event and meeting with telcos from across the APAC region. Hope to see you there next year!

Por qué Analíticas es la respuesta para el Director Financiero moderno?

Analytics, Telecom Insights & Analytics

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Como bien dijo Gordon Gekko, en la película Wall Street (1987), “La mercancía más valiosa que conozco es la información”. Afortunadamente para las compañías de comunicaciones y sus Directores Financieros, no carecen de esta “mercancía valiosa”, la cual pueden aprovechar mediante analíticas.
Descubre cómo los Directores Financieros pueden aprovechar sus datos mediante analíticas de telecomunicaciones, para tomar mejores decisiones que impulsen el crecimiento y mitiguen los riesgos, viendo la grabación del webinar llamado “No te quedes atrás: una guía de Directores Financieros para aprovechar las analíticas avanzadas”, que tuvo lugar el 14 de diciembre.

But let’s go back a moment.
The world of telecommunications, as we know it, is evolving and, with it, the role of Financial Directors is also undergoing a drastic change. Its role is no longer limited to focusing solely on past performance, numbers and financial information, but the mandate seems almost universally exceeded, and the CFO also needs to provide information on where the business is going and how fast it is doing.
The participation of the Financial Directors in the corporate strategy has also become an integral part of the work, since they now have the capacity and the mandate to contribute directly to the business management, as well as to review and report on their performance. All this means that today’s Financial Directors must be more strategic and need to ensure that they are more aligned with the strategic imperatives of the business, and this requirement places the Financial Director at the focal point not only for the presentation of financial reports, but also also for management reports, in addition to maintaining a solid and healthy balance sheet.
But, as we know, the dynamic nature of the telecommunications environment poses multiple obstacles to the modern CFO, which includes – but is not limited to – the following:

_ CFOs today must ensure that they are able to increase the margin and return on profits.
It is a well-known fact that ARPUs have been steadily declining in all regions of the world and, together with the slow growth of revenues, is leading to a steady erosion of margins since 2010 in most regions. In the midst of these challenges, the Financial Directors’ mandate to increase margins and profit performance is increasingly critical and difficult.

_ Organizational attempts to increase revenue are deflating due to errors and leaks.
Addressing Income Leaks is a major concern for telecommunication operators, and it is fast becoming a mandate for Financial Directors, considering that currently most of the RA teams report to them. Given that Income Leaks have a direct impact on revenue growth, the CFO’s role now is to take a proactive stance in the treatment of any error or loss.

_Evaluate the risks and develop measures to prevent security breaches.
Like revenue leaks, security breaches and telecommunications fraud can cost operators a lot, and is an obstacle to ensuring that CFOs maintain a solid balance sheet. $ 38.1 billion (USD) were lost due to fraud in 2015 and, although the number is decreasing, Telcos continue to feel the impact of losing money due to fraud, and the task of resolving this lies with the Chief Financial Officer.

_Increase Capital Expenditures during a period of decreased income.
A recent survey conducted by TMForum, led by Subex, revealed the following conclusions:
– 1 in 3 operators does not measure the returns on investment in CAPEX.
– 77% of respondents consider that the inappropriate use of assets leads to an increase in costs.
– 55% of respondents believe that network planning is based on assumptions.
– 64% believe that capex planning is driven by technology and not by business objectives.
On the other hand, CSP’s global revenues decreased by 5.3% for the year ended March 2016, while gas responded to volatility and speed of change
The signs indicate that revenues from traditional services will stabilize in the next 10 years. In fact, some analysts anticipate that revenues from traditional communications services will be reduced by 50% from current levels by 2025. This means that CSPs must embrace the digital revolution and can no longer be stupid but must be seen as smart tubes By offering digital services and being seen as DSPs or even LSPs (Lifestyle Service Providers) to capital increased, raising capital expenditures (capex / revenue) to 19.8% for the year.

_Increased competition, even from OTT players.
According to Ovum, it is expected to cost the Telcos a combined total of $ 386 billion between 2012 and 2018.

_Responder to volatility and speed of change.
The signs indicate that revenues from traditional services will stabilize in the next 10 years. In fact, some analysts anticipate that, by 2025, revenues from traditional communications services will be reduced by 50% from current levels. This means that CSPs must embrace the digital revolution, and can no longer remain dumb channels, but should be seen as smart tubes that offer digital services, and be seen as DSPs or even as LSPs (Lifestyle Service Pviders).
And the challenges do not end there! Today, CFOs need to devote more time and effort to managing the future rather than residing in the past and, therefore, need to further analyze the analytical data to connect the dots and predict the future. To their advantage, Telecommunications Financial Managers possess unprecedented amounts of data, from multiple sources, including customer data and network data, and can take advantage of this data through the power of telecommunications analytics.
If taken advantage of in the right way, through the application of advanced analytics, Telecommunications Financial Managers will be able to address the challenges they face and achieve business results that align with their agenda, through the generation of actionable telecommunications knowledge. CFOs can have a 360 degree view of their business context and identify and even proactively predict problems, opportunities and threats, and help them address them before internal audits. For these reasons, it has now become the mandate of the CFO to conduct analytics for both strategic and operational decision making.
Through the generation of Telecommunications Knowledge, an Advanced Analytics Solution can help Financial Managers to meet the growing expectations placed on changes in their roles, enabling them to:
_Proactively predict and direct resources to counteract risks and take advantage of opportunities .
_ Reduce uncertainty by anticipating disruptive changes, and respond and adapt to create growth opportunities.
– Predicting Income and Fraud Leaks to face risks proactively.
_Predending redundancies and reassigning budgets to reduce and control costs.
_Increase the impact of pricing decisions and promotions through optimization.
The Advanced Telecommunications Analytics solution has the scope to help the Financial Directors of telecommunications operators to meet business objectives drastically, and we have even seen or, better said, helped a Level 1 CSP, based in North America. , to save costs, simply by helping them resolve disputes. Through the generation of telecommunication knowledge, the association helped the CSP improve its ratio of predicting and resolving disputes to 9x, which in turn helped them save up to millions of dollars. This is the power of the Advanced Telecommunications Analytics solution.
For more information on how CFOs can take advantage of telecommunication analytics to maximize revenue and mitigate risks, see the webinar’s recording “Do not Stay Back: A Guide for Financial Managers to Take Advantage of Advanced Analytics,” on March 16. February.

Why Analytics is the Answer for the Modern Day CFO?

Analytics, Telecom Insights & Analytics

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As Gordon Gekko from the movie Wall Street (1987), rightly said, “The most valuable commodity I know of is information.” Fortunately for telecom operators and their Chief Financial Officers, they possess no dearth of this ‘valuable commodity’, which they can leverage through telecom analytics

Find out how CFOs can leverage their data through telecom analytics, by gener to make better decisions to drive growth and mitigate risks by viewing the recording of the webinar on ‘Don’t Get Left Behind – a CFO Guide to Leveraging Advanced Analytics’, which took place on December 14th .

But let’s take a step back for a moment.

The telecom world as we know it is evolving, and with it, the role of the CFOs has also been undergoing a drastic change. His role is no longer confined to be solely focused on past performance, on the numbers, and on financial reporting, but the mandate seems almost universally to have been exceeded, with the CFO needing to also provide information about where the business is going and how quickly it is getting there. [1]

The CFOs involvement in corporate strategy has also become an integral part of the job, with CFOs now having the ability and the mandate to contribute directly to the direction of the business as well as reviewing and reporting on its performance1. This all means that today’s CFOs need to be more strategic and need to ensure that there is better alignment with strategic business imperatives and this requirement puts the CFO at the focal point for not just financial reporting but also managerial reporting, along with his core objective of maintain a strong and healthy balance sheet.

But, as we know, the dynamic nature of the telecom environment places multiple hurdles in the face of the modern day CFO, which include, but are not restricted to the following:

  • CFOs today need to ensure that they are able to increase margin and earnings performance
    • It is a well-known fact that ARPUs have been steadily declining in every region of the world, and coupled with slow revenue growth is leading to a steady erosion of margins since 2010 in most regions[2]. In the midst of these challenges, the mandate of CFOs to increase margins and earnings performances in becoming increasingly critical, and difficult.
  • Organisational attempts at growing revenues are being deflated by errors and leakage
    • Addressing Revenue leakages are a major concern for telecom operators[3], and is quickly becoming a CFO mandate considering currently most RA teams ultimately report to the CFO[4]. Considering that revenue leakages have a direct impact on revenue growth, it is now the role of the CFO to take a proactive stance in addressing any errors and leakages.
  • Assessing risks and developing measure to prevent security breaches
    • Like Revenue Leakages, security breaches and telecom fraud can cost operators heavily, and is an obstacle in the way of ensuring CFOs maintain a strong balance sheet. $38.1 Billion (USD) was lost to fraud in 2015, and though the number is decreasing YoY, telcos are still feeling the pinch of losing cash to fraud, and the task to resolve this lies with the CFO.
  • Increasing Capital Expenses during a period of decreasing revenues
    • A recent survey that was conducted by TMForum led by Subex revealed the following findings:
      • 1 in 3 operators do not measure returns on CAPEX investment
      • 77% of the respondents believed that inadequate asset utilization leads to increase in costs
      • 55% of the respondents believed that network planning is based on guesses
      • 64% believed that capex planning is driven by technology and not business objectives

Moreover Global CSP revenues declined by 5.3% for the year ended March 2016, while capex increased, pushing up capital expenses (capex/revenues) to 19.8% for the year.[5]

  • Increasing competition, even from OTT players
    • Which according to Ovum, is expected to cost Telcos a total combined $386 billion between 2012 and 2018
  • Responding to the volatility and velocity of change
    • The signs are that revenues from traditional services will plateau over the next 10 years. Indeed, income from traditional communications services is anticipated by some analysts to decline by 50% from current levels by 2025. This means that CSPs need to embrace the digital revolution, and can no longer remain as dumb pipes but need to be seen as smart pipes by offering digital services and be seen as DSPs or even LSPs (Lifestyle Service Providers)

And the challenges don’t just end there! Today CFOs need to spend more time and effort managing the future rather than dwelling in the past, and hence need to take an even closer look at data analytics to connect the dots and to predict the future. To their advantage, telecom CFOs possess unprecedented quantities of data, from multiple sources including customer data and network data, and can leverage this data through the power of telecom analytics.

If leveraged in the right way, by applying advanced analytics, telecom CFOs will be able to address the challenges they are facing, and achieve business outcomes that align with their agenda, through the generation of actionable telecom insights. CFOs will possess the power to have a 360 degree view of their business context and identify and even predict issues, opportunities and threats proactively, and will help them address them before internal audits. For these reasons, it has now become the mandate of the CFO to drive analytics for both strategic and operational decision-making.

By generating Telecom Insights, an Advanced Analytics Solution can help CFOs to meet the increasing expectations placed on their changing roles by enabling them to:

  • Proactively predict and direct resources to counter risks and leverage opportunities
  • Reduce uncertainty by predicting disruptive changes and respond and adapt to create growth opportunities
  • Predict revenue leakages and fraud to proactively address risks
  • Predict redundancies and reallocate budgets to reduce and control costs
  • Increase impact of pricing and promotion decisions through optimization

Advanced Telecom Analytics has the scope of helping CFOs of telecom operators meet business objectives drastically, and we have even witnessed, or rather helped a Tier 1 CSP, based in North America save costs by purely helping them resolve disputes. Through the generation of telecom insights, the partnership helped the CSP improve their hit ratio of predicting and addressing disputes to 9x, which in turn helped them save up to a few million dollars. Thus is the power of Advanced Telecom Analytics.

To find out more about how CFOs can leverage telecom analytics for revenue maximization and risk mitigation, view the recording of the webinar on ‘Don’t Get Left Behind – a CFO Guide to Leveraging Advanced Analytics’, on December 14th.

[1] http://www.ey.com/gl/en/issues/managing-finance/the-dna-of-the-cfo—perspectives-on-the-evolving-role—the-cfo-s-contribution

[2] https://www.strategyanalytics.com/strategy-analytics/news/strategy-analytics-press-releases/strategy-analytics-press-release/2015/01/23/global-trends-for-mobile-operators-show-stagnant-revenues-and-declining-margins#.WD-iJeZ9600

[3] https://www.kpmg.com/Global/en/IssuesAndInsights/ArticlesPublications/global-revenue-assurance-survey/Documents/global-revenue-assurance-survey.pdf

[4] https://www.kpmg.com/Global/en/IssuesAndInsights/ArticlesPublications/global-revenue-assurance-survey/Documents/global-revenue-assurance-survey.pdf

[5] https://www.ovum.com/research/communications-service-provider-csp-revenue-capex-tracker-1q16/

IoT Settlements – Leverage the world of opportunity

General, Partner Settlement

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The Scenario

Of late IoT has gained a lot of attention and every operator is at least thinking of leveraging this latest platform to offer innovative products, but the big question is how?

Many operators are relying on their vendors to come up with IoT use cases, the challenge here is that even the Vendors are still in process of deep diving as IoT is still a niche market.

One of the major factor that makes IoT an unknown area is the lack of visible use cases to be seen in our day to day life, though the developed counties have made significant progress, developing world is yet to embrace the “Smart” systems. With lot of emphasis on Smart cities, IoT business is here to stay.

When it comes to IoT Settlements, both Telcos and Vendors should start thinking out of the traditional wholesale approach. Telcos are looking for vendors who can support them with their traditional as well as new business areas with the centralized solution.

The Concept

Understanding “Internet of Things” concept is very simple, it is a network of “Things”. Things are physical objects that can be added to a network, have sensors and can be controlled using software. These things can be as common as day to day devices like a Fridge, a Car, a thermostat and so on. The purpose of connecting ‘things’ is to have a centralized access to their features and to control enormous data they are capable of producing.

One very obvious fact that can be identified from IoT is to have a medium for keeping things connected. This creates an immense opportunity for telecom operators to provide medium for supporting the connected items. According to Gartner by 2020, the Internet of Things will grow to 26 billion units installed which excludes connected PCs and smartphones. This will add $1.9 trillion to the global economy. Intel estimates 31 billion devices to be connected by 2020. According to Cisco by 2020, 50 billion devices will be connected, whereas Morgan Stanley feels that the number is much higher and it can go up to 75 billion.  The good news is, there is a substantial growth opportunity for everyone, right from smart device manufacturers to the smart service providers everyone can get their share of business from IoT.

The Process

Let us consider an example of a smart home. There are multiple interconnected devices which are installed for security, entertainment, utility etc. These are all connected to a centralized hub, which in turn is connected to the IoT platform. IoT platform consumes the data generated by these smart devices for insights and to make sense of this huge data.

To establish this network of devices connected to hub and IoT Platform, internet is needed. This gap is filled by the Telcos. So bringing in smartness requires lot of partners to work together. Let us enrich above example to get more clear understanding of the multi partner involvement.

A  leading furniture retailer has introduced a new Smart Home Solution, where consumer can install smart devices such as TV, Fridge, Air conditioner, Washing Machine, Radio, lighting solution, thermostat and security solution. Finally these devices are connected to hub to have a centralized control of the devices.

A smart Hub ensures all smart devices speak the same language, this enables user to remotely control the devices even if the user is far away from the home. To bring in more intelligence the data gets transmitted from smart devices to the IoT Platform. The IoT platform analyzes the data, apply rules and makes devices more smart based on the usage patterns.

Finally the most important piece of this setup is facilitated by a Telecom operator to ensure internet connectivity for all the devices to communicate. Telecom operators can also bundle voice and SMS services along with data to take actions based on the defined rules. E.g. in case there is a security breach, device can initiate a call & SMS to the owner and insurance company to inform this breach.

So in this particular eco system, we have seen multiple partners working together to establish a Smart Home solution.  Similarly there are multi partner IoT use cases for Smart Car Fleet, Smart Healthcare, Smart Grids, etc. In all the IoT use cases irrespective of the catered domain, Telecom Operators and IoT platform vendors will always play a significant role, directly or indirectly they will contribute to billions of dollars in the IoT economy.

For a Telco, providing backbone is not the only important thing in IoT space. With the complex partnership models, Partner Management, Billing and Settlements are other crucial activities that will result in the Cost and Revenue identification.

The Solution – Partner Management, Billing & Settlement

With the cut throat competition and reducing margins in the traditional Wholesale business, operators are adding new dimensions to their business with immense revenue generation capabilities of Internet of Things.

A new age partner Settlement solution cannot limit its functionalities to just traditional business models. There is a requirement for settlement solutions to be more agile in accepting and delivering new business requirements with short time to market. If we talk about IoT for a Telco, now partners are not limited to Voice or Content providers, rather the list is getting much diversified with partners coming in from various domains like health care, agriculture, utility, etc.

For a smart home solution, a telecom operator can provide IoT backbone to a furniture retailer , where the Telco will ensure internet connectivity and will enable IoT platform in collaboration with a cloud computing platform. Here the furniture retailer becomes the Telecom operator’s customer and the cloud platform provider is Telco’s vendor.

Partner Management & Settlement solution deployed at Telco should take care of partner (Customer & Vendor) lifecycle management, easy on-boarding, business transparency along with IoT billing & settlements. Partner Settlement solution should also be capable of managing plethora of Meta data that will be provided by the IoT Platform for billing and Partner analysis. The volume of IoT data can be much more compared to traditional usage data.

The system should also be capable of providing innovative products and should do billing accordingly. Key point here is to have personalized plans created based on the business need. Some of the products that can be offered as a part of IoT platform are:

  1. Flat Rating – Flat rates for data, call and SMS for each units.
  2. Fixed Charges – Fixed product price for unlimited data, voice & SMS
  3. One time & Recurring Charges – Product to support one time and recurring charge capabilities
  4. Device Based – Charge based on number of devices connected
  5. Slab & Tired based – Data, Voice and SMS to be defined, rates varies based on the slabs & Tiers
  6. Pay-as-you-go – Charge only based on the usage, deduction from Prepaid Balance
  7. Cross Domain Products – IoT clubbed with content or other interactive services

IoT billing & settlement is not just limited to the Telco and their direct partners, it has to be extended to the associated MVNOs in from of Billing as a service. There can be a multi-level partner involvement as well, say based on the movie genre analysis information available in meta data generated by a Smart TV, a latest movie can be suggested for subscription through an entertainment company , and hence the entertainment company can become 2nd level Advert/Content partner.

IoT is still evolving, there can be many aspect that are yet to be explored. This is the right time for Telcos, platform and equipment vendors to start investing in IoT to stay ahead of the competition.

Infographic :

partner-settlement-solution

Customer Analytics: Securing our Future

Analytics, Telecom Insights & Analytics

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In the previous blog in this series I looked at how the use of persona, and creating customer journey maps for those persona, can give new insights on how to engage customers. By collecting customer data and tracking user interactions across all touchpoints, it’s possible to not only create an revealing profile of a customer’s interests and behaviour, but also better understand if the products and marketing are addressing customer’s wants and needs.

Technology is now rapidly opening up new sources of customer data including everything from health and well-being apps to our children’s activity online. Soon our heating systems, cars, refrigerators and every other connected appliance that’s about to hit the shelves will be churning out a stream of data back to the marketing departments of big corporations. The effective use of this big data undoubtedly has great potential to improve our lives, but there is also an increased risk that the individual’s privacy could be compromised, or the data could also be used to discriminate against an individual unfairly. In a recent case in the UK vulnerable customers were advised to buy energy on tariffs that were far higher than others available.   The same is true of insurance and medical care, and many cases exist where it’s been found that corporations are exploiting data to prey on the vulnerable. Add to this the substantial risks of identity theft and fraud as a consequence of data breaches, and consumers could be forgiven for feeling anxious about how well their data is being protected, and how it’s being used.

In an effort to stop corporations from exploiting big data negatively and better protect consumers the European Union has raised the bar on data protection by drafting the the General Data Protection Regulation (GDPR). This new set of rules will apply not only to countries within the EU, but also to companies operating outside the EU, if they have networks or trade data with partners within the EU. Enforcement is expected to start in the spring of 2018.

The European commission’s website states that:

The objective of this new set of rules is to give citizens back control over of their personal data, and to simplify the regulatory environment for business.

Furthermore, as reported by consultancy group itgovernance,

The Regulation will enforce tough penalties – proposed fines up to 4% of annual global revenue or €20million, whichever is greater

For a large multinational the fines could get very substantial and significantly impact on share prices.

The GDPR sets out 8 Data Protection Principles that must be followed. The ICO, UK’s independent Information Commission, has provided clarification of how these principles need to be applied. For example, Principle 1 refers to Processing personal data fairly and lawfully. As described on their website,

In practice means that you must:

  • have legitimate grounds for collecting and using the personal data;
  • not use the data in ways that have unjustified adverse effects on the individuals concerned;
  • be transparent about how you intend to use the data, and give individuals appropriate privacy notices when collecting their personal data;
  • handle people’s personal data only in ways they would reasonably expect; and
  • make sure you do not do anything unlawful with the data

Perhaps one of the key new areas is in the use of big data and analytics for customer profiling. This is covered under Principle 6 of the GDPR under the somewhat obtuse description of ‘automated decision making’. ComputerWeekly have produced a number of documents and guides to help businesses to understand how the GDPR will affect them. In one of their latest blogs they explain

The regulation introduces a number of restrictions on profiling, including the right for an individual not to be subject to a decision which significantly affects the individual and which is based on automated profiling. In many cases, profiling will only be permitted where the explicit consent of the individual has been obtained. 

The implications for targeted marketing are unclear, but potentially significant, as it makes companies accountable for ensuring that customers

  1. Are made fully aware of exactly how their data will be used
  2. Explicitly agree to the way in which the data will be used
  3. Do not suffer any negative consequences from the use of their data.

As ComputerWeekly reports

These restrictions are likely to have a considerable impact on businesses engaging in, for example, big data analytics, as well as more general business activities, such as credit scoring and employee monitoring

In an article by the International Association of Privacy Professionals , they add that data subjects (customers)

…may also request to know the purposes of processing, the period of time for which data will be stored, the identity of any recipients of the data, the logic of automatic data processing, and the consequences of any profiling.

Corporations are now in real danger of drifting into a situation in which they are in breach of the new regulations, face substantial fines and seriously damage customer relations.

In the final blog of this series I will be looking at how customers are becoming increasingly concerned at the inability of corporations to keep their data safe, and how high publicity data breaches are eroding public confidence.

Customer Analytics: Walking in the Customers Shoes

Analytics, Digital

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In the first blog in this series on customer analytics, the technique of Customer Journey Mapping (CJM) was discussed as a way to follow how customers move from one touch point to the next, and track their emotional well-being during those interactions. In the last blog I described how using a persona to represent a group of customers would allow marketing to get a better understanding of customers. In this blog I will explore how Customer Journey maps can be created for persona to visualize an idealized journey for the group represented. This is now becoming a well-accepted technique for not only improving user experience in software design, but also in the design of products, digital and conventional marketing channels, architecture and many other areas.

There are two basic approaches for creating persona. One is to base the persona on in-depth research of the customers within a market segment, and the other is to base the persona on intuition, sometimes referred to as a provisional persona. In reality, it makes most sense to use a combination of research and intuition, and then verify the persona with those who have front line contact with customers. Generally customers belonging to a company’s biggest market segment would be targeted first and a primary persona is created to represent them. If the team creating the persona do not have direct knowledge of the customers in that segment then they will need to conduct research to understand the values and motivations of the group.

Once a persona has been defined then it’s possible to look at how the company would engage that persona in a sale, and the hope is that the persona would follow each engagement at every touchpoint, even long after they’ve made the purchase and are using the product. The framework for this is known as the Customer Lifecycle. There are many versions of this but they all share some basic stages, as described by Jim Sterne and Matt Cutler in a paper called “E-metrics, business metrics for the new economy

  • Reach: Trying to get the attention of the people we want to reach.
  • Acquisition: Attracting and bringing the reached person into the influence sphere of our organization. 
  • Conversion: When the people we reach or have a more established relationship with, decide to buy something from us.
  • Retention: Trying to keep the customers and trying to sell them more (cross-selling, up-selling).
  • Loyalty: We would like the customer to become more than a customer: a loyal partner and even a ‘brand advocate’ Moments of truth

This can be represented either horizontally or in a circular lifecycle type chart

The Customer Life Cycle – Source: E-Metrics Business Metrics for the New Economy by Jim Sterne and Matt Cutler

The persona journey describes how it’s anticipated that a particular persona would move through the lifecycle. It would describe the channels through which it’s expected they are made aware of a product, how it’s expected they would research the product and what would motivate them to make a decision to buy. Key points in the journey where customers decide whether to continue or abandon the process are known as ‘Moments of Truth’, a term coined by Jan Carlzon, the well-known CEO of SAS Airlines who turned the company around in just a couple of years.

Walking in the customers shoes in this way is not easy, and would normally be done as a workshop with representatives from across an organisation, but it’s an exercise that can provide many useful insights. Service quality gaps, cross channel alignment, ways to better engage customers and align internal teams are just a few of the many benefits that come from journey mapping. When idealised journey maps are compared with the actual journeys that customers take then many preconceived ideas about how customers see and engage with the company may get thrown out and fresh ways to engage, retain and acquire new customers be discovered.

In the next part of this customer analytics based series of blogs I will be looking at the security implications of big data and advanced customer profiling, and how regulators around the world are trying to protect an individual’s right to be treated equally by large corporations.

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