The telecommunications space plays a critical role in facilitating modern communication, especially during these uncertain times. With all the social distancing measures and quarantine restrictions, it has become essential to keep people and businesses connected to each other—be it with their families, colleagues, or customers. This surge in demand for connectivity has transformed the telco landscape in numerous ways.

As an industry that capitalizes on the transfer and exchange of data, the telecom sector has a wealth of data on their hands they can use to stay ahead of the competition — network performance, product usage, customer information, billing details, and more. This constant influx of data presents a lot of opportunities for telcos, but only if organizations adopt strategies that aim to make this data accessible and useful.

To transform your retail organization and be more customer-centric, you need to improve in areas where it counts: areas that impact your customers’ experience. The lifeblood of any retail organization, your customers expect a lot from the industry, especially with all the recent changes in shopping habits and the economic landscape in general. Customers are more discerning these days, and it will be up to retail organizations to cater to their needs and expectations.

At its core, healthcare organizations revolve around the patient. Like any other business, the healthcare industry is consumer oriented. There are customers to take care of—literally—which is why it’s important to create a great patient experience. However, with COVID-19 putting a lot of pressure on the industry, maintaining a patient-centered approach has become a challenge.

Feedback is crucial to continuous improvement. When an employee wants to be more effective at their job, they would benefit from knowing what they’re good at and where they need to improve. The same goes for your products. To consistently offer quality products, knowing what your customers think is key. Customer reviews are a goldmine of valuable big data and insights that all retail organizations should tap into.

When people ask you what EMR means, how many hospitals are in the area, or what’s the best way to understand your patients, you tell them “google it.” But when they ask you how to do something—track your heart rate, book an appointment, pay bills, consult with a doctor online—you say “you know, there’s an app for that.” Because most likely, there is. There’s an app for almost everything these days—and the healthcare industry is no exception.

In recent years, there’s been an increasing demand for data scientists left and right, across industries and across departments. In the same vein, companies are getting more and more data than they know what to do with. In fact, according to IBM, 90% of the data in the world today has been created in the last two years alone. To put this influx to good use, organizations are turning to data scientists.

Predictive analytics is a complex process that involves many steps and procedures—from collecting and preparing data to communicating findings through eye-catching dashboards. But there’s one stage that data scientists enjoy doing more than others: predictive modeling and algorithms. As an integral part of data science, modeling involves building a solution, mining the data for patterns, and refining algorithms.

In a world filled with volatility and unpredictability, organizations must be prepared to deal with disruption. This is especially true for the manufacturing sector, where the slightest error or variation can have a ripple effect across the production line and the organization. For example, as the global pandemic closed restaurants and crowded grocery stores, supply chain management had to be reimagined.

For many businesses, data has become the new currency. Organizations have come to rely on data insights to monitor the health of the business, track productivity, and identify key opportunities to optimize outcomes. However, implementing and maintaining analytics efforts can come with its own set of challenges. In order for organizations to make the most out of data, reliable data management is key. In this regard, many are turning to cloud-based analytics models for scalability.