Tower business transformation through power of data management and applied analytics

The fast-paced marketplace of today demands quick decision making. The decisions must be based on facts. These facts are covered deep inside extensive volumes of complex business data of organizations. In what capacity can generous volumes of data from organized and unstructured sources be translated? The solution is to first identify interconnections and relationships between the data and develop algorithms for defining the future of business and gain competitive edge.

Data and analytics are directly proportional to each other, with the immense growth of data, organizations can realize higher value only if the depth of analytics is increased.

Key points and advantages:

• 360 degree perspective of the organization
• Identify hidden patterns, behaviors and relationships in the data
• Identify opportunities to optimize costs across the value chain
• Provide better insights for improved decision making

Need for Analytics in the telecom tower industry

Telecom Tower Infrastructure providers, who want to be innovative and maximize their revenue potential must have the optimal solution so that they can harness the volume, variety and velocity of data coming into their organization and leverage on actionable insights from that data. Telecom Tower Infrastructure providers are sitting on terabytes of data that are stored and scattered across the organization. For simpler and faster processing of only relevant data, they need an advanced analytics driven data solution that will help them to achieve timely and accurate insights using data mining and predictive analytics.

Understanding value of data:

Data Foundation:

Data is central to any decision or action. Once a strong data foundation is built, the next logical step is to run analytics to obtain actionable insights to enable decision-making and produce business growth.

Every portion of data has value:

The collection of data alone cannot change an organization’s performance. Businesses need to follow, collect and store all of it, and they need to filter out noise to derive value.

Value can be classified as:

Information, which provides details about what already has been done and accomplished.
Knowledge, which comes from the insights gained from data that explain why something happened or future outcomes.
Intelligence, based on historical data, which leads to new meaning for future actions.

Journey of Analytics:

Telecom Tower Infrastructure providers can start off with the basic steps of analytics such as Descriptive and Diagnostic analytics, since these steps help to generate a complete overview of the organization. They contribute towards the objective of improved decision making and achieving profitability.

journey
WWH (Why, What, How) Approach:

Descriptive analytics:

• Why?
It mines historical data to provide managers with information that enable them to take effective informed decisions. It combines data from disconnected sources and then provides complete information on previously occurred events.

• What?
Set of techniques used to explore any kind of data. It answers the question, “What Happened?” – looks at data to describe current business situation.

• How?
Divides data into small data sets and generates standard reporting, dashboards and alerts.


Diagnostic analytics

• Why?
In-depth analysis of data to find the patterns and determine if there is a correlation between the two data points.

• What?
Answers the question: why did it happen? This is the next level of analysis where the data points are further analyzed to get to the root cause of the problem.

• How?
Provide key metrics by understanding the pattern of data.
Involves Adhoc Reporting: Provides customized insights and recommendations based on each data point.
The next level of analytics, i.e., Predictive and Prescriptive analytics predict and provide forecasts by building business rules and models that optimize business functions.

Predictive analytics:

• Why?
Comprise of statistical and data mining techniques that help in analyzing current and historical data to predict future trends, events and behavior patterns. These techniques are used to predict future outcomes.

• What?
Answers the question: What is likely to happen? The next level of analytics which predicts the future outcomes by analyzing current and historical data.

• How?
Detect trends, clusters and exceptions and provide dashboard view of future outcomes to users.

Prescriptive analytics:

• Why?
It suggests a set of actions based on the outcomes of both descriptive analytics and predictive analytics. It provides a reliable path to an optimal solution and enables managers to take decisions in a large and complex data environment.

• What?
Answers the question: How to improve? The next level of analytics which simulate various outcomes to choose the best or an optimal solution.

• How?
Analyze the previous outcomes and suggest the optimal solution for improved decision making via dashboards, reports.

Infozech’s Solution: Delivering defined outcome through applied analytics, improving efficiency and ROI

Infozech’s solution combines cloud based analytics with a managed services approach, applying intelligence to improve the efficiency of telecom operations and energy management. Infozech’s proven solution, manages over 150,000 sites in India.

Infozech’s Solution: Translating insights from analytics into actionable strategy to reduce opex

When we collect data, it comes to us in a raw form. The real insights come from bench-marking that data against another source, that’s when the learning starts happening. For example it might be a simple case of comparing data from the same site last week or to the same week last year, or comparing with another similar site. We slice and dice data to benchmark against all sites with similar gensets, similar tenants or which are serviced by the same maintenance teams. It’s our experience that the people who collect data are not necessarily comfortable slicing and dicing that data. The data slicers are often based in the corporate headquarters and can be somewhat separated from the reality in the field. Infozech’s managed services enable data analysts to slice and dice as they want, to store and reconfigure analyses for future actions. Infozech’s product provides customized reporting to tower infrastructure providers for improved decision making and achieving profitability.

In Conclusion: Advanced analytics is necessity for all Tower Infrastructure Providers

In this era of globalization, Advanced analytics is necessary for all tower infrastructure providers to be always aware of the current status of their business. To stay in business and compete with its competitors, all the tower infrastructure providers should use third party analytical engine. Recent innovations and trends in analytics provide more scope for the managers to effectively use various tools in order to achieve better business value.

Infozech’s Telecom Framework products includes below mentioned modules to address various business challenges:

1. Billing (Retail, Wholesale and Roaming):- Encapsulation of Traffic Analysis, Financial Reporting, Invoice Reconciliation, Prepaid Customer Handling and commission calculation.
2. Integrated Customer Life Cycle Management: – Allows analyzing the subscriber usage and filters as per segmentation rules. It recommends plans in a speedy fashion based on subscribers need.
3. Analytics: – The solution uncovers hidden clues, complex problems, and factors critical to manage / reduce risk.

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