Almost every business in the developed world now depends on data in some way. It may be as simple as the data generated from the transactions of buying and selling, or it could be much more complex, such as coordinated medical records needed to keep people healthy.
But while data has a value in the sense of it being information, it also has an additional value from the intelligence that can be gained through analysis and comparison. It’s with those insights that businesses can make the right decisions, improve experiences, and optimize how they operate.
In this blog post, we’ll highlight four areas where data intelligence makes a major difference.
What is data intelligence?
Data intelligence enables the process of multisource data, it generates meaningful insights that will help business to make valuable decisions. With data intelligence you can combine unstructured data and text analytics results for predictive analytics and it gives a real-time statistical analysis of structured or unstructured data to understand data patterns and dependencies.
Why do we need data intelligence?
We need data intelligence to understand data, particularly big data. It helps business owners make smart decisions about driving their business forward. Examples of why data intelligence is needed include: artificial intelligence, insight generation, intuitive visualization, and data-driving decision-making.
What can data intelligence do?
All good retailers use online sales platforms to good effect, using data to target the right customers with the right products at the right times, and understanding which products sell better than others, where and when. But this is only scratching the surface of what’s possible with data in retail.
By using data intelligence, retailers can follow up cart abandonment and interest on a particular web page with personalized offers. They can also blend the physical and virtual through ‘try-on’ services, where clothes and furnishings can be digitally modeled on photos of the customer and their home respectively. Analytics can also be used to improve the in-store experience, as customer data can be linked to store appointments, so that retail staff can focus on the products that the customer is most interested in.
At a time of great turbulence in the job market, employee experience has come under the spotlight as a means for employers to differentiate themselves to the best and brightest talent around. As well as greater flexibility around when and where they work, many employees also want more flexibility and autonomy in how they’re paid. Some find that getting a pay packet at fixed intervals compromises their finances towards the end of each month, or when unexpected bills arise.
One innovative solution to this is on-demand pay, where employees can accrue wages day by day, or shift by shift. They can then independently view their earned wages on an app, from which they can withdraw however much they need, whenever they need it. The data generated from their use of this app can be put to good effect by payroll and HR teams, who can identify trends that might suggest an employee is having trouble managing their finances. They are then able to offer focused support and training to the employees who need it most.
A constant concern for commuters who drive is the presence of potholes on the roads, and how long it can take maintenance crews and local authorities to get them fixed. But thanks to data intelligence, cities equipped with smart technology are able to cut these response times, as well as address issues before they can have an impact.
Mapping software can enable the capture of every element of a street environment in detail, and automatically analyze it for potential safety hazards, or poor road surfaces where potholes could develop. Not only does that allow local authorities to take a proactive approach to maintenance, but it also allows them to assess road conditions remotely from a computer, rather than through the time-consuming approach of inspecting each problem area in person.
Reshaping the office
With many more people adopting flexible working patterns, the old office ideal of rows of desks full of people working nine-to-five is increasingly becoming outdated. Businesses therefore need to not only explore ways in which employees can book workspaces for the days when they’re in the office, but also understand how the office layout can be changed to support the needs of flexible workers. And because flexible working differs from one business to another, understanding how to get this right isn’t always clear.
This is where a workspace booking solution with embedded analytics can make such a positive impact. Not only can it allow employees to book the spaces they need for the times they need them, but every booking generates valuable data on workspace usage that can be analyzed and form part of detailed reports. Those reports can then inform effective reshaping of the office environment, such as replacing some workstations with informal collaboration spaces, and scaling the number of meeting rooms up or down to match demand.