Hello Experts,
I would like to discuss with you a common scenario to most cellular operators: halt on investments.
In a scenario where new investments are few or none, what are the options operators have to “keep walking”?
For example, how to use radio optimization team and current resources?
Some ideas to enhance user experience?
Or to increase traffic and/or revenue?
Maybe a side project?
As there are lots of experts here, I would like to hear some suggestions if possible, some “out of the box” idea.
In short: how operators can reinvent themselves in a low budget scenario?
Thanks in advance.
I think the way Optimization teams (and other resources from Operators/Vendors) can reinvent themselves is by shifting (or at least learning) some data science (machine learning, artificial intelligence).
It’s time to adopt modern technologies and techniques to stay relevant. Learning Data Science can be good for any other area they may go (not only Telecom Optimization), as data science has proved its high value and efficiency. Nowadays data is a fuel needed for any successful company.
Telecom companies operate with vast communication networks and infrastructures with the intense data flow. Processing and analyzing this data with the help of data science algorithms, methodologies and tools find practical application.
Within the telecom industry data science applications are widely used to streamline the operations, to maximize profits, to build effective marketing and business strategies, to visualize data, to perform data transfer and for many other cases. Key activities of the companies working in the telecommunication sector are strongly related to data transfer, exchange, and import. The amounts of data passing through various communication channels are getting larger every minute. Therefore, old techniques and methods are no longer relevant.
Of course, Telecom companies have a big range of challenges (solve problems, control or even prevent from happening) where data science can be explored:
- Fraud detection
- Predictive analytics
- Customer segmentation
- Customer churn prevention
- Lifetime value prediction
- Network management and optimization
- Product development
- Recommendation engines
- Customer sentiment analysis
- Real-time analytics
- Price optimization
In following article you can see a little more detailed explanation for some of the most relevant and efficient data science use cases in the field of telecommunication (for the several use cases above, and how to get real benefits from each one):
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Data Science is one of the many emerging technologies. Others include:
- 3D printing
- Bitcoin Blockchain
- Mobile wallets for fiat
- Electric cars and battery design
- Disturbed autonomous systems
- Cryptography
I have deliberately mentioned crypto graphy separately. In my opinion, crypto graphy and 3D printing are undervalued technologies.
Today, every company is trying to push it’s data on cloud. As data scientists, we understand that data is more precious than the dollars. Consequently, it’s wrong to upload the data on cloud without encryption.
In my opinion, the next big wave in data science would be to encrypt the data before putting it on cloud.
And there’s not much skilled resources on Cryptography.
3D printing is going to completely disrupt the construction industry.
Bitcoin would dismantle the paper money in due course of time. Oops… I am not supposed to talk about bitcoin 🤦♂.
I just wanted to say that there are many technologies we can switch to.
Data Science is surely a rewarding experience and career.
But there are some other exciting technologies too.
Network security! It’s going to be a one hell of a technology as money gets stored in mobile wallets.
People are okay if their data gets into others hand. But nobody would be ok if the money gets stolen.
How many of us have lost money due to exchange hacks in cryptocurrency.
So… Cheers… there are infinite possibilities and options for us to move to. Telecom industry enabled a lot of technologies. But now it’s going to stop seeing the exponential growth in opportunities we had seen in the last two decades.
This is good for us as it encourages us to learn new skills and explore new opportunities.
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Well, on how to use radio optimization team and resources,
1.we are bringing good energy saving features where 2 carriers will be shutdown at night when load is relatively low and site runs on remaining 2 carriers.
2.We dont purchase any tool for optimization like Ericsson’s tool for driveless optimizations, even we dont have mapinfo. My operator believes in ownership and in house production so we have many in house tools, for data analysing we use RQA periodic measurements to collect rrp, rsrq, ta samples for neighbors to know overshooting, coverage overlap between 850 and 2300 band to do load balancing between two bands. With this we are finding many issues and our team keeps walking.
3. As its hard to get new towers , we are replacing 80W RRUs to 160W to extend coverage, bringing ESCs which are for extending coverages etc
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Ya agree with you, we must move from traditional way to modern way. Some usecase is how to prevent subs churn, detect anomaly network behaviour, congest detection, market segmentation and marketing strategy, etc
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