Beyond The Big Data Buzz: Professional Services

When you read or hear news stories about the imminent takeover of robots and algorithms that will eliminate jobs for human workers, many times the first examples given are blue-collar jobs like factory workers and taxi drivers. But even highly skilled professional services like accounting, law and architecture are seeing massive change thanks to advances in data, analytics, machine learning, robotics and artificial intelligence. Increasing automation and massively increased computing and analytic power allow professional service providers to deliver a smoother, faster and more efficient service, whether that service is designing a building or preparing for a big law case.

In accounting, software can automatically import transactions, keep track of digital receipts, automate payroll and keep track of taxes. But even more complex tasks like auditing, regulatory compliance and trend analysis can be carried out by computers these days.

The legal profession is also on the cusp of some important data-related developments. In the discovery phase of a lawsuit, lawyers and paralegals may have to sift through thousands, even tens of thousands, of documents. Sophisticated databases can now use big data techniques, including syntactic analysis and keyword recognition, to accomplish the same tasks in much less time. In fact, the technology exists for computers to accomplish even more complex tasks like reviewing precedent and case history, and even drafting legal briefs. The ability to predict the outcomes of major cases is another area in which data, particularly predictive analytics, can play a significant role; in fact, a statistical model created by researchers at Michigan State University and South Texas College of Law was able to predict the outcome of almost 71 percent of US Supreme Court Cases.

In the world of construction, building designers, engineers and construction firms are already starting to move into arenas such as real-time, cloud-powered analytics. Not only do these methods help to drive innovation, speed up the design process, reduce waste and reduce costs across major projects, they also help foster collaboration between the interested parties: the architects (who want to unleash their creative energy), the engineers (who have to try to make it all fit together and stay standing), and the owners (who are usually desperate to keep costs under control).

Telecoms, too, is seeing huge benefits from data analytics, particularly when it comes to uncovering critical insights about customers, markets and sales. US telecom company Sprint has access to vast amounts of user data, thanks to its huge network of users. Three years ago, it formed a subsidiary, Pinsight Media, to help capitalize on that data and inform advertising decisions. In the three years since Pinsight was established, the company has gone from serving zero to six billion ad impressions per month.

Data is also dramatically changing the nature of call centres. Natural language processing (NLP) is what allows an automated system to properly direct your call when you speak into the phone. It used to be that you had to use the exact word or phrase, saying accounts or operator in order to be routed properly. But with the growing sophistication of NLP algorithms, systems can now interpret long strings of words, like, I have a weird charge on my bill I want to talk to someone about, and route that caller to the correct department. Speech analysis goes beyond what you say to under- stand how you say it, analysing the callers tone, vocabulary, sentiment, and even silences to gauge emotion and satisfaction.

Finally, software providers like Microsoft are increasingly gathering and leveraging user data and using this information to better understand how people use their products and, sometimes, provide targeted advertising. Software providers are also increasingly moving away from a product-based model towards a cloud-based software-as-a-service model, allowing them to gain a far more accurate picture of when, how and why their product is used. These insights are helping companies like Autodesk create a better product and provide an improved service for customers.

(Source: Marr, 2019)

Big data in human resource management refers to the use of many data sources to evaluate and enhance practices including recruitment, training and development, performance, compensation, and overall business performance. It also has attracted the attention of HR professionals who now can analyze mountains of data to answer key questions regarding employee productivity, the impact of training on business performance, employee attrition and more. With the growing amounts of employee, customer, and transaction, human resources are compelled to divert themselves towards the newer technologies to aid faster decision-making amid a volatile business environment. With such a huge bunch of data resources, HR professionals can evaluate and enhance practices including recruitment, training and development, performance, compensation, and overall business performance.

Evaluate how big data can transform human resource management practices (streamlining hiring process, enhancing employee motivation and engagement, utilizing appropriate resources, increasing employee retention, and future casting).

(Inscriptions: Predictive analysis, analysis and monitoring, and reporting.) (20marks)