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Tag Archives: ROC

Addressing the Trust Gap. It is Possible

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. 

Aditya Ghosh

Aditya heads Sales & Presales for Analytics for Subex in Africa. He has been in the analytics industry for 6+ years, with experience in Retail, Pharma, Technology and Telecom domains. He believes that Analytics is delivered right only in an Iron-Man setup (Man-machine model).

Selling devices – A boon or bane for Telcos?

Smartphone flashes in mind, when device is mentioned.  Devices, however, are a large ecosystem beyond smartphones – a range of equipment like dongles, routers, customer premise equipment (CPE) and IP phones, to name a few.  Devices are a great tool for telco to lock their customers in. For instance, the bundled offers with contracts spanning months provide predictable revenues for the telco’s.

The next wave of opportunity

With IoT and 5G making inroads, telco’s are preparing for the next-generation devices for home and office networks. A lucrative opportunity for telcos, as devices are critical to the IoT/5G penetration. Newer devices will be introduced, like small cells to boost network capacity and improve indoor coverage. It’s no wonder that telcos are investing into devices.

Are telcos benefiting from devices ?

Devices are an attractive opportunity as they improve customer stickiness and ARPU. Devices are good promotional tools to attract new customers and gaining traction even in emerging economies. Many customers extend their relationship with telcos beyond contract period.

Yet, procuring, selling and managing devices is riddled with risks. Fraud, leakages and unmanageable debt are hampering the revenues and profits.

A survey across telco’s states:

telcos stats

What are the risks?

Telco’s on an average spends 20% of their OPEX on procuring and servicing devices. The entire supply chain covering the forward and reverse logistics is prone to risks. The supply chain not only involves stakeholders within the telco (marketing, sales, operations, logistics, finance), but many external parties –manufacturer, supplier, financing partner, distributor, shipping partner, warehousing network, retail agents, repair/refurbish partner, and the end-customer.

risk

The technology stack is complex with at least 10 different applications and platforms involved. Leakages of stock in ordered vs received, inventory gaps, devices ageing at inventory, gaps at POS are a few technological risks to highlight.

Bane to boon – Manage the risks

How could telco’s control the risks & leakages, and make the best of the opportunity? It is important that Telcos have Device Assurance strategy in place to manage the device related risks. Stay tuned for more updates about Device Assurance Solution.

Revanth Sharma

Revanth Sharma is a seasoned professional who specializes in Risk Assurance in Telecom . He has over 10 years of experience in the Telecom industry and has a vast exposure to customers from all regions. He currently works as a Director- Business solutioning & consulting, managing various product & services portfolios for emerging markets at Subex.

Cash in on Reverse Logistics

Reverse logistics has long been the problem child of supply chain management. Increasingly that child has been in need of some serious help. This is due to two factors. The way in which the internet has transformed how we shop, and the short lifecycle of consumer goods. Although most consumers still like to shop in high street stores to find the products they like, at least 8% of sales are now from consumers just clicking on a picture to buy a product, comfortable in the knowledge that they can return it if necessary. In most countries, consumers have a legal right to return goods purchased on the internet. Many retailers now even offer free ‘try-before-you-buy’ returns, but the processes for managing those returns, known as reverse logistics, are far more fragile, costly, and susceptible to issues than the generally well-controlled forward logistics processes. Although return rates vary widely across different verticals, the average return rate has been calculated to be around 17 to 18%.

Brightpearl

Source: Brightpearl

Reverse logistics faces complex issues due to the ad hoc way in which consumers return items and vulnerabilities in the returns processes. Because reverse logistics is not seen as a revenue-generating process, it sometimes doesn’t get the attention it needs, but recently it’s been getting more widely recognized as having a key role in the company’s profitability. Having efficient processes for collecting, re-selling or recycling used items can bring in additional revenue and improve a company’s bottom line. There are other important reasons for giving more attention to reverse logistics.  Consumers are now judging companies on their green credentials, and consumers are aware that many electronic devices contain some highly toxic chemicals. Providing a channel through which old devices can be traded in and reliably recycled is a positive selling point. The efficiency of the returns process also has a significant impact on customers impression of a business.

Although the ‘returns revolution’ impacts all retail lines of business, high-value consumer electronics are especially prone to issues in the returns process.  Huge volumes of handsets, set-top boxes, routers, even TV’s and laptops, are now being returned through a multitude of channels for a variety of reasons. Warehouses may receive thousands of such goods per week. Most of those devices may still be working and able to be resold, but tracking such devices back from customers, assessing their viability for resale, refurbishing, repackaging, and then re-distributing them, is a substantial challenge.

The problems begin as soon as a customer says they want to return a device. Whether it is because the device is faulty, unfit, incorrect, unwanted, or because they’re terminating their contract, they must provide notification that the device is getting returned. Agents must correctly capture the details of why the device is getting returned and issue an RMA (Return Merchandise Authorisation). This will trigger a complex sequence of processes to terminate services in the network, calculate bill adjustments, prepare downstream systems for receipt of the returned devices, update inventories on receipt, manage the inspection, refurbishment, and resale of those devices, and potentially issue replacements for faulty devices. Depending on factors such as contract, warranty, device status, termination type or customer rating, customers may be liable for additional charges or eligible for compensation.
Reverse Logistics

Typical return channels would be to send a device by courier, return it to a shop, or a technician may return the goods.  Whatever the channel is, devices will often arrive without a clear indication of which customer account they relate to.  Returns to stores are particularly problematic with agents failing to scan in barcodes or register returns correctly. In-store systems may not be able to record IMEI, IMSI and/or serial numbers, and there is no motivation for staff to label returned devices accurately.

With so many moving parts it’s no surprise that many devices become stranded or lost along the way, and customers getting charged incorrectly. Operators have been known to write off more than $5+ million in lost devices per month.

One solution is to implement automated controls that provide monitoring across all systems in both forward and reverse logistics, thus assuring that devices can be monitored from the initial order in CRM, in and out of warehouses, with couriers, shipping, refurbishment partners, finance companies and activation status in network service provisioning.  With monitoring systems in place that can even detect the physical location where devices are installed, it’s possible to validate inventory, bill customers and partners accurately, prevent fraud, recover maximum value from returned devices and understand why devices are getting returned.

Subex provides ROC Device Assurance solutions to operators around the globe, helping to track down missing devices, reconcile and correct billing, CRM, provisioning, distribution and inventory systems with world leading discovery and reconciliation capabilities.

Mark Jenkins

Mark Jenkins has worked in the IT industry for over 15 years as a BI and Analytics consultant, and more recently as ROC Product Manager for Subex Ltd. He has designed and deployed solutions for global companies in many sectors including Insurance, utilities and telecommunications. Mark holds a BSc Hons in Computer Science from Manchester University (UK).

Zen and the art of Root Cause Analysis

Our story begins with Farmer Joe who has a beautiful daughter Janet. Farmer Joe decides to bequeath the family decorative pin to Janet on her 20th birthday. Now Janet, in a fit of unbridled joy decides to run around a haystack holding the pin towards the heavens. Suddenly,in a scene far too clichéd to be coincidence, she trips and the pin falls into the haystack…

Now begins the daunting task of “finding the pin in the haystack”. Janet is faced with a dilemma which would be quite familiar to RA analysts the world over – how do we find the pattern which highlights the root cause (or the pin, if you are a farmer’s daughter who goes by the name of Janet) within a world of millions of CDRs.

Of course, the solution is to cut the haystack into smaller cubes and search smaller segments for the pin. Does this sound familiar to you, my RA analyst friend? It should – because this is the way we attempt to find the root cause today. When your system presents you with millions of CDRs (or, God forbid, meaningless summaries), we tend to break them into smaller sets which have seemingly similar patterns. Then begins the back-breaking task of finding the elusive pattern that indicates the root cause – an endeavor that involves quite a few cups of strong coffee, pointless mails and shattered dreams regarding deadlines and analyst efficiencies.

But hey, this is how we do Root Cause Analysis the world over right? We would reduce our effort by managing the problem size right? Well, it gives me great pleasure to say that the winds of change are blowing. Today, I would like to introduce to you to a fundamental paradigm shift in Root Cause analysis which would effectively transform the way we do RA.

Let’s imagine for a second that Janet decides to find the pin by placing a powerful magnet over the haystack. Consider how much time and effort she saves, as compared to breaking the large haystack into smaller stacks. Consider how sure this solution is, as compared to the possibility of not finding the pin even after breaking the haystack into smaller segments.

Now imagine such a magnet for RA. A magnet that presents the analyst with all the hidden patterns in a problem set (discrepant CDRs). Imagine how this would change your day in terms of boosting analyst efficiency, achieving cost efficiencies as a department, being prepared to handle new and upcoming technologies and always staying one step ahead of the curve.

That magnet has a name, and its name is “Zen”. Subex recently launched ROC Revenue Assurance 5, and along-with RevenuePad (which my colleague Moinak would write about), Zen is one of the fundamental pillars of this ground-breaking solution.

Zen is an automated Root Cause Advisory engine which provides, for the first time ever, machine intelligence for pattern identification and presentment. What makes it revolutionary is that the engine is programmed to sniff out patterns with minimal involvement from the analyst. Give Zen two data sets, and it will tell you exactly why some CDRs in data set 1 are not present in data set 2. This also involves telling the analyst what percentage of the total data set can be linked to any particular pattern. Since pictures speak louder than words, here is a sample illustration:

Zen is essentially a data analytics engine for ROC Revenue Assurance 5. Based on the discrepant sets identified as the result of an audit, Zen automatically fires up the pattern analytics engine. As Zen works on identifying the patterns, it also works on linking the patterns to specific CDRs (to ensure that an audit trail would be maintained). Finally, Zen presents the analyst with a comprehensive view of:

  • All identified patterns in the discrepant data set
  • Distribution of how many CDRs are linked to which pattern
  • Historic event indicators to further guide the analyst towards the root cause

Zen is keyed towards two “Intelligent” actions:

  • Pattern Analytics
  • Analyst Feedback integration

We refer to Patterns as “Areas” and the learning from past investigations as “Reasons”. Why do we need both, you ask? The answer is fairly simple – the same pattern (or Area) might have presented itself for very different “Reasons”. A simple example of Subscriber profile between HLR and Billing might clarify this point.

An analyst, on performing the HLR vs Billing subscriber reconciliation, finds that 20 subscribers on the HLR are not present on the Billing platform. Now, in the absence of provisioning logs, he/she might surmise that this is a simple case of provisioning error and forward the information to the relevant teams.

However, if the same discrepancy is seen next week for the same set of subscribers, it might be prudent to address the possibility of internal fraud as well. Here we see an example where the same pattern (20 subscribers are missing repeatedly in billing but are provisioned on the network) might be due to two distinct “Reasons” – Provisioning Error or Internal Fraud.

Zen helps you tie it together. Reasons are incorporated into the Zen engine based on “Acknowledgments” received from various teams. This helps to ensure that “False Reasons” are minimized. In this manner, Zen becomes a repository of Analyst intelligence to address the world-over issue of Knowledge Management in RA.

Zen is a virtual analyst who never sleeps, eats or goes on vacations. For sure he will never leave the team (taking his accumulated knowledge with him).

In conclusion, I want all of us to take a moment to step into Janet’s shoes. The pin is in the haystack, and the stack is getting bigger and bigger all the time (due to burgeoning volumes and technology/product complexity). The timelines to find that pin are ever-shrinking, and cost reduction is the call of the hour globally.

How is your team planning on finding that pin?

Ashwin menon

Ashwin joined Subex in 2006 as a part of the Implementation team for Revenue Assurance & Fraud Management. Over the years he has worked with cross-geographical teams to drive value discovery and creation for telecom operators across Middle East, Africa and APAC as a delivery SME and a Business Solutions Consultanct. Beyond his work in Subex, he has been involved in some of the most seminal Revenue Assurance public domain centers (both in terms of his work on popular RA blogs as well as his co-authored work on Revenue Assurance for Telecom Operators). He regularly speaks at various industry events on areas pertaining to Business Optimization.

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