Improving business services with intelligent data

Business services is a growing and highly profitable industry sector. Companies within the sector are consequently looking to extend and refine the services they offer. Data provides a key tool in a business’s evolution and helps differentiate the services it can offer. The challenge is to use that data intelligently to improve service quality and gain a competitive advantage.

Business services occupy a major place in modern economies

In the UK, the professional and business services sector employs around 15% of the total workforce in a wide range of roles. Recruitment, IT, logistics, transportation, property management, training, communications – these examples reveal the diversity of services offered by businesses to other businesses. Yet despite the variety and breadth of the sector businesses providing services are connected by common experiences and challenges. One biggest of these is how to put the increasing amount of data generated by business interactions to intelligent use.

IT is changing business

IT features in every business arrangement from simple email or text correspondence to fully automated processes. Digitization, automation, and, now increasingly, Artificial Intelligence are transforming the efficacy and quality of transactions bringing efficiencies in business services and processes. 

But despite the successful deployment of technology employed there remains work to do to gain the full benefits of IT. The application of technology generates data – and increasingly Big Data. Within it are the seeds of further business benefits, but the task is to collate and analyze that data and implement its findings.

Business analytics produces intelligent data

Data analytics is a specialized area that offers the tools and techniques to utilize the mass of data organizations accrue while conducting their business. Analytics can be descriptive, diagnostic, and predictive, providing the hard data to allow organizations to make informed, evidence-based business decisions.  

Analytics can, though, go one step further and recommend changes based on its analysis of the data. Prescriptive analytics offers guidance on which strategies to adopt, which investments to make, and how to optimize performance. In other words, the application of analytics can transform raw data and make it intelligent.

Intelligent data delivers results

Analytics leads to cost savings by offering businesses increased visibility into their processes. Greater insight into the working of the business facilitates the optimization of processes and better allocation of resources. External data on market trends and competitors’ performance can be mined to improve strategic planning. The quality of the data delivered by business analytics results in better decision-making grounded in historic and current evidence. Data on customer preferences, needs and satisfaction levels can be used to enhance the client experience.  

The cumulative effect of making data intelligent is to give the business the support it needs to strengthen its market position and challenge its competitors.

Making changes require upskilling

As data analytics encourages changes to the way the business operates training must support and enable employees to take on new roles and responsibilities. In cases where processes become completely automated this might involve the re-skilling of an entire cohort of employees. In many cases retraining will mean upskilling people to use new IT applications and play a proactive role in carrying out new procedures or providing upscaled services. Elearning provides a flexible, agile and time-efficient way of providing up and re-skilling across business disciplines and sectors.

Learning benefits from analytics too

Learning analytics has become a key subset of general business analytics. As more learning is digital, the more learning related data is generated. Data from various learning activities and experiences can be integrated and aggregated using the xAPI standard in a Learning Record Store (LRS). Learning analytics tools available with the LRS can then be used to make intelligent use of the data collected. Learner analytics provides a comprehensive and in-depth picture of your training provision. It will deliver data on learner take-up, progress, and experience. In turn, intelligent learning data helps quantify training effectiveness and ROI.

Analytics improves training

Analytics provides clear evidence of whether training is working or not. It offers insights into how learners prefer to learn leading to an improved learning experience. Analytic data highlights business critical skills gaps across the organization showing areas where upskilling or recruitment is required. More granular data and recommendation features allow for personalization with content, activities, pathways tailored to the performance needs of individual learners. The quality and breadth of the data put business training on an evidence-based footing making learning more effective and relevant.  

Learning analytics is of a piece with business analytics in making organizations fit to compete in current and future business climate. It makes it easier to align L&D policy and practice with strategic business goals.

Intelligent data can make the difference

New technology is changing the landscape for business services. It’s creating expectations of higher levels of service amongst clients and is transforming in the way the industry works. But as well as disrupting the status quo, new technology also provides the tools and, critically, the data to allow businesses to learn, adapt, and compete in this challenging new environment.

Learning Pool is helping organizations in business services create a competitive edge with the use of intelligent data. Find out how.