Category: ACT

Most organizations use analytics to improve their operations to enhance business performance and growth. However, through our experience of working with telecom organisations across various geographies, we have witnessed that analytics in many cases is done in an ad-hoc manner rather than in a planned phase. This results in organisations not witnessing the kind of return they were expecting from their analytics investments. An Analytics Maturity Assessment (AMA henceforth) helps in identifying such pitfalls and avoiding them. Few of the pitfalls that AMA helps in identifying are:

1. Data Issues & trust: The root of any analytics project is the Data element. It is important that the end user does not have any form of data trust issues when it comes to their data. Proper data capturing, storing, infrastructure design, validation etc. are important dimensions which AMA investigates with proper checks and balances based on industry standards.

2. Lack of Clarity: The first step to having clean data comes from having a good understanding of the data. There are basic graphs, queries, questions that every data analysis requires at the start of any project. For companies to be truly data driven, a Data Analysis pack consisting of the above elements and beyond is necessary. AMA checks these points to help figure out whether the first cut is robust enough. This understanding, the results of such a pack, is essential not only for the analytics team but helps business users as well gather lots of useful insights.

3. Lack of Business Understanding: Analytics is a means to an end and not an end in itself. The intention is to help the organization improve on its top line, bottom line and operational efficiency. This is not possible unless the analytics team has a good understanding of the business as well the business team clearly understands what analytics can bring to the table. Synergy between the two is needed for implementable outcomes. The analytics solution should answer the questions that the end user wants to know. AMA helps in avoiding this pitfall or checks the status quo by having multiple checklists such as SMEs, trainings, meetings, presentations on this dimension.

4. Improper Implementation: After what is to be done is clear, how it is done is essential for effective implementation. Ad hoc project work and repetition of same mistakes are cost centers for organizations. There must be standard practices for project implementation.

5. Information Asymmetry: Having to constantly reinvent the wheel is another cost factor which takes the essential time of resources. This issue is usual the result of teams working in silos and not functioning as a larger team. Often similar analytics projects are undertaken in different verticals such as say finance and operations. This is another grey area which AMA helps in identifying and avoiding.

6. Missing dollar accountability: Many organizations do not have long term vision in place. In these cases, analytics becomes good to have but it remains just a cost center. The vision and purpose of analytics needs to should come from the top and be clearly identified and communicated. Each project’s expected outcomes should be predefined and once implemented, its ROI calculated. This is essential for the integration of analytics into the DNA of the organization for it to be able to make a string contribution to the growth story.

Conclusion:

It is essential for every organizations to take stock of the situation after certain intervals. It is even more important when trying to inculcate something very different and new within the organisation to bring about a mindset/cultural change. Most of organizations are investing in analytics but find using it effectively difficult. AMA helps in streamlining this change. It helps in asking pertinent questions and figuring out the change methodology. As noted above, there are quite a few pitfalls of not having an AMA for an organization, and not having an AMA in place can be expensive considering the associated risks.

To understand more on how you can adopt an AMA within your organisation, view a recent webinar we had conducted on the topic.

Click here to view the webinar

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!