Making sense of data
2019-08-13 4 min read
By 2020, researchers estimate that each person on earth will generate 1.7 megabytes of data every second. This vast amount of data can help businesses to gather information, analyse performance and make important business decisions, but only if the data is in a format that they can understand.
Businesses across all sectors are considering how they can benefit from digitisation. By introducing digital platforms and processes to the business, managers can improve efficiency and reduce costs to remain competitive in their respective sector.
Digitisation can impact a variety of areas in the business, such as storing documents, managing workflow and allowing employees to access data remotely. Businesses can also collect huge amounts of data from a growing number of sources to monitor business performance, productivity and consumer behaviour. For example, manufacturers can now fit sensors to machines around the facility to monitor the environment and the equipment’s condition to ensure everything runs at full capacity.
Do you speak data?
Leadership teams require insight into what their data means, so that they can use it to make strategic decisions. To do this, they can employ data scientists to help collect and analyse data, interpret the findings and create a report that management can read easily. However, this can be a time-consuming process and by the time management sees meaningful data it might be too late to prevent an issue from occurring.
For example, manufacturing companies can attach sensors to a robot to monitor machine condition. The management team must be able to read the report to understand when a machine is not performing at full capacity. At this point they can contact an industrial parts supplier and source a part that will fix the machine, preventing the risk of site downtime.
Cut out the middle man
By investing in the right technology business leaders can reduce the time it takes to interpret important data. For example, businesses can invest in a management and data analytics platform with natural language processing
Natural language processing (NLP), is a branch of artificial intelligence (AI) that helps computers to understand human language. NLP is not a recent discipline and has been used since the 1960’s to help people search databases in their natural language. For example, it is the reason that search engines understand your queries and generate relevant results.
NLP helps to break down barriers between humans and technology, improving communication and productivity. The AI system can then produce real time reports from the collected data in natural language. Instead of relying on a data analyst, managers can see these reports as soon as the data is generated, detect patterns and trends and make important business decisions in near real-time.
IBM’s Watson, for example combines artificial intelligence and analytical software to help businesses analyse huge volumes of unstructured data. The platform also uses natural language processing, deep learning algorithms and tone analysis to make recommendations on how to present the data.
Using platforms like Watson allows businesses, particularly manufacturers to improve productivity. Engineers can use Watson to catalogue, prepare and analyse data shared across a business. Its natural language understanding allows Watson to understand unstructured data, extract the keywords, trends and semantics and interpret it in thirteen different languages.
Business leaders can also use NLP to improve efficiency and accuracy when completing administrative tasks. For example, businesses that rely on handwritten forms or human produced content may find that forms are illegible or may be lost during movement between employees. Businesses also have to input this large amount of data into a computer manually, which can be time-consuming and repetitive for employees, increasing the risk of error.
Handwriting recognition technology removes the need to input data manually. Employees can scan a document and the software uses character recognition to convert the text into a digital format, saving time.
Businesses should consider how they can best use the copious amounts of data that we generate daily. By investing in data analysis platforms with natural language processing capabilities, business leaders can access real-time information and make decisions that will improve productivity and increase competitiveness as more businesses digitise.