Most organisations generate vast amounts of data, which can add immense value to the organisation if it is captured, stored and analysed in the right way. For example, a company involved in the logistics industry generates data around aspects of the business including supplies, orders, time taken for distribution, and issues in the supply chain, to name just a few.
Using the right type of software, the organisation can capture, store and analyse this data. With the right analytics they can gain invaluable insights into their operation, helping teams to decide where to focus attention to increase value.
All industries have benefitted from big data, data lakes and storage management, but there are a few specific sectors in the region that are realising huge gains, including oil and gas, retail, logistics and manufacturing. These sectors are heavily dependent on intelligence to remain competitive, and advances in big data and data analytics are increasingly able to help provide this type of intelligence.
Big data and data analytics are at a nascent stage in their development, even though they are already adding immense value to organisations across industry verticals. As with any relatively new technology, there are limitations and constraints. At present, the constraints are primarily related to culture and training.
A company can have the best data analytics solution available, but it still requires a degree of human interpretation from people within the organisation, after which the organisation will also need to execute a course of action based on its interpretation of the data.
These are two areas that could potentially limit the potential of big data and data analytics. Thankfully, both challenges can be remedied through training and by efforts to implement best practice within the organisation.
Data analytics tends to give better results when greater amounts of data are gathered and analysed. This opens-up the opportunity for organisations within different sectors to share a certain amount of anonymised data to gain even greater insights about their industry. For example, companies involved in hospitality can use shared data to gain a greater understanding about demand peaks and optimal room rates at different times of year.
Infor is working with large organisations across sectors including utilities, real estate, oil and gas, manufacturing, retail, leasing, distribution and healthcare. Customers in these sectors are using solutions that rely on big data and data analytics.
Infor is working with Saudi Bugshan, a major diversified business group in Saudi Arabia; Supertech Group, an industrial supply company based in Dubai; and major utilities including Ras Al Khaimah Wastewater Agency and Samra, Jordan’s leading wastewater treatment plant.
All of Infor’s cloud-based solutions – whether in Enterprise Asset Management EAM, Enterprise Resource Planning ERP or Supply Chain Planning – make extensive use of big data, in that they enable organisations to collect, aggregate and analyse their data and help them better understand their business and sector, and make better informed choices.
Data lake capabilities are built into all of Infor’s cloud-based solutions. Infor Data Lake, a scalable unified repository for capturing an organisation’s enterprise data, is built into Infor’s cloud operating platform Infor OS.
Among Infor’s solutions that benefit from big data and data analytics capabilities are: Infor M3, an ERP tool designed for medium to large global manufacturers, distributors and after sales service providers; Infor EAM, an enterprise asset management solution; and Infor CRM, which helps to give a full view of customer interactions. Other solutions that use big data include Dynamic Enterprise Performance Management and Infor LN.