Harnessing the Power of Business Intelligence in the Call Center

Call CenterHaving the power to make timely and knowledgeable decisions is a crucial part of succeeding in the call center environment. Business intelligence (BI) allows organizations to harness this power, giving leaders greater insight into performance and talent attributes where greater efficiency and productivity can be achieved among individuals and throughout the entire organization.

In spite of the well-known advantages of BI, it still remains new territory for many organizations. The following places a spotlight on BI and its ability to promote positive change in many aspects of the call center.

Defining Business Intelligence

The goal of BI is to sift through big data and use the information gained to aid in the decision-making process, ensuring that organizations remain competitive and responsive to upcoming trends and sudden changes in marketing strategy. BI also seeks to foster consistent improvement, promote beneficial business activity, and allow leaders to identify and tackle potential problems before they have an opportunity to sideline operations.

BI has always been around in one form or another, but the rise of cloud-based call center technology has made it much easier to use. In the days before modern tools, much of the data needed to facilitate BI would have to have been pulled, analyzed, and reported manually. As a result, organizations that needed BI most often lacked the agility to benefit from it.

The Role of BI in the Call Center

Integrating BI into the call center allows leaders to harness the power of big data for their daily operations. By using analysis of agent performance and how it could potentially affect business outcomes in real time, it becomes much easier to quickly and easily address performance concerns. The end result is months of improvements that now only take weeks to achieve.

BI also introduces a historical perspective to call centers. For instance, improvements in scheduling, resource allocation, and cost forecasting often come from examining historic data. Trends gleaned from this data can be put to good use when adjusting hiring needs, agent schedules, and additional training.

Employing historical and real-time BI allows organizations to become more responsive to changes in customer demands, allowing call center agents to pivot quickly in order to meet those changes.

Quantifying Success

Organizations should remember that BI isn’t a smoking gun when it comes to producing success. It’s important to define, monitor, and measure the metrics that are essential to the call center’s overall effectiveness. These metrics can be used to identify areas in need of improvement and generate new data sets for further analysis.

For more information on how business intelligence can benefit your call center operations, contact us at ROI Networks for a no-obligation consultation.

Cloud Convergence: Harnessing and Simplifying the Power of the Cloud

CloudWhether technology-focused or not, in today’s environment, all businesses have technical challenges to meet. Data is fundamental to evaluating markets, planning for growth, improving internal process efficiency, and dozens of other tasks across all areas of business. And with the great complexity of business data comes great complexity in data management. One way of meeting these challenges is to leverage converged data infrastructure in the cloud.

What is converged data infrastructure?

Converged infrastructure is a way of providing tested configurations of applications and services. With a converged system, technologies such as data storage, database queries, networking architecture, and other useful features are bundled together to address as many business needs as possible. This allows companies to outsource much of the costly setup and integration work, as well as allowing – in some cases – converged infrastructures to be replicated across providers.

Not all converged infrastructures, however, are provider-agnostic. Solutions from companies such as Amazon and Google may tie businesses in to their specific business model, and make it more difficult to replicate environments elsewhere. Whether or not this is desirable depends a great deal on what ancillary services a business needs to integrate, and how their disaster recovery plans are shaped.

What considerations go into selecting cloud infrastructure and converged data infrastructure?

Three major considerations should guide the cloud converged infrastructure decision: cost, management, and security.

  • Cost. Cloud services perform well against services managed in-house because they tend to cut down on up-front expenses, and they can also reduce the need for a company to have a dedicated team of IT professionals and managers. However, care needs to be taken with savings in the cloud: some cost-saving measures, such as shared hosting environments, come with tradeoffs in the form of security. And the cost advantage of outsourcing data expertise and management is only a wise investment if the service provider chosen has the expertise and availability to meet all of a company’s needs.
  • Management. Regardless of how experienced a service provider is, they can’t take on all facets of data management for a company. Companies need to research and make informed decisions about a number of aspects, such as what services are to be considered core, what converged stacks are under consideration, how important server location is, what namespace access (as well as replication and failover) is going to be, and how performance is going to be evaluated to determine whether the move to the cloud is a success. This may be a different skillset than a traditional IT manager may have, and businesses may need to invest in training to bring business sense and awareness to technical employees.
  • Security. Some converged data infrastructure providers have excellent physical security and data encryption, and those companies with strong security practices should be sought out and preferred. But businesses also need to consider what security policies they’ll put in place, such as requiring access to cloud data to use VPN connections, or requiring strong passwords and up-to-date anti-virus software on personal devices in a BYOD workplace. Data security also needs to be taken in to account in the form of disaster recovery: for example, can a converged infrastructure solution be replicated across providers, in the case of a provider-wide outage?

The Final Word

There is no one-size-fits-all solution to data management. Converged data solutions, however, do offer a degree of standardization and ease of access which can be extremely powerful for businesses.

ROI Networks simplifies the complex world of business collaboration and communication technologies. Contact us today to learn more.

Big Data and the Future of Healthcare

Big DataBig data has gradually become part of everyday life. From wearable devices and smart phones to vehicles and more, data is collected from just about everywhere and everything. The healthcare industry is slowly coming on board, beginning to use big data in a myriad of ways.

Fraud Prevention

One of the biggest problems in healthcare is fraud. Identity theft, misuse of benefits, and provider payment scams are rapidly increasing, which results in billions of dollars in losses each year. Programs such as Medicare are often the target of such crimes and have taken action by investing in computer systems designed to reduce this hemorrhage of funds. Analytics derived from big data are instrumental in these efforts, able to detect savvy criminals and collusion between patients and providers.

Predicting the Future

Predictive analytics uses big data to foresee the health issues of patients. Information acquired from social media, business networking sites, medical provider visits, family health history, and more are gathered and analyzed. Intricate algorithms assess this data and signal the physician that a medical issue could be oncoming. This advanced notice allows earlier treatment and a much more positive outcome for the patient. In addition, this could help reduce the cost of healthcare by treating patients before they develop a chronic, expensive condition or emergency.

Privacy Concerns

The internet holds a wealth of information that is both public and private. When using predictive analytics to forecast healthcare needs, it is easy to see how privacy is compromised. Private information must be shared with insurers and healthcare providers to truly reap the benefits of the technology. Eventually it may be necessary to create specific privacy laws to help protect patients in this new world.

Other Notes

These programs are still in their infancy, so it’s difficult to know if big data and predictive analytics will ever affect the price of life and health insurance coverage. Current social programs spread expensive claims over a large group of insured patients to attempt to cap premiums. As the political arena changes these programs may as well, making future insurance and healthcare costs difficult to predict.

Big data in healthcare is just beginning to show its power. As technology advances, it’s very likely that this information will be used to save patients and money across the industry. For more information about the future of healthcare IT, contact ROI Networks.

The Impact of Big Data on Education

Big DataAn entire industry has been created around managing, analyzing, and transforming raw data into actionable information. One area where big data has begun to make a perhaps unexpected impact is the education sector. At almost every grade level from kindergarten to graduate programs, educational institutions are discovering the importance of this increasingly valuable asset.

Creating Jobs

The proliferation of big data necessitated an increase in workers with the background to assess and translate files into something understandable and meaningful to organizational leadership. Data analysts, statisticians, architects, stewards, and change agents are all in higher demand as a result of this evolution. Providers of education must develop programs that teach these skills and will accordingly look for trainers, professors, and specialized school administrators who understand data-related careers. They must ensure that growing market needs can be filled by graduates with the appropriate background.

Strategic Planning

When big data is processed and used in purposeful ways, it can have a major impact on the future growth of an organization. Educational institutions are no exception to this. Student results, performance measurements, and retention statistics may be used to assess the effectiveness of a school’s current programs and campaigns. Program gaps and unfulfilled student needs can be identified and corrected. Other subjects could be introduced to attract new students.

Student and Parent Engagement

Keeping the interest of students, especially in earlier grades, can be difficult. These years are critical to the trajectory of a child’s life and the encouragement and involvement of parents is vital. Where big data is instrumental here is in helping to diagnose a child’s stumbling blocks. The school can then convey those details to the parents for assistance and support. The more quickly these obstacles are addressed, the more successful the child may be in overcoming them.

Approaches to Teaching

The performance results that can be obtained via big data are a useful way to tailor teaching methods precisely to each student. Such a high level of personalization improves the outcome of the learning experience. Additional delivery methods such as educational video games and software make learning interactive and fun for youth who might otherwise be disinterested.

Taking the use of big data a step further, some educational software applications use predictive analytics to change lessons to better suit the user. These can identify knowledge gaps as the user works through the content. Such programs are built to accommodate learners of varying skill levels and learning styles so that they absorb knowledge as successfully as possible.

Simplify Student Moves

Historically, if a student transferred to another educational institution, the process of giving the new school their files was cumbersome and time consuming. Big data has made that nearly instantaneous, ensuring that the student and his or her teachers have what they need at the new facility.

Big data is gaining importance across all industries, and education has begun to share in that experience. Through obtaining and assessing student data, the educational experience is enriched. For more information on the role of data in education, contact ROI Networks today.