Increasing Effective Decision Making by Utilising Data

The amount of data now being used and stored every day would have been incomprehensible only ten years ago, with a total of 2.5 exabytes of data, the equivalent to 2.5 billion gigabytes, being produced each day. The name aptly given to this large amount of data that is both structured and unstructured is big data. As we are now operating in an environment centred around big data, the amount of information flowing round and through our systems at any one time is remarkable.

How to use your data to your advantage

With this challenge to manage data also comes the opportunity to use the information to the advantage of your business, Intelligent machines are now being created to deal with this ever increasing amount of data. IBM, for instance, recently unveiled the supercomputer Watson, which can ingest data at the rate of 67 million pages a second. It is obtaining this ever-increasing flow of data from the millions of connected devices in the Internet of Things. The purpose of this latest IBM innovation is to establish a ‘question and answer’ dialogue between it and humans, whereby Watson will run unimaginable amounts of data and answer in plain speech and in real time. It can use intelligence to streamline data processing tasks such as demystifying incentive plans and analysing sales team’s effectiveness.

Perhaps we should not be surprised. It is the direction of travel for analytics, and it has been made possible by the seemingly infinite capacity of the cloud with its interconnected stacks of thousands upon thousands of servers.

[easy-tweet tweet=”How can intelligent machines aid in tailoring big data for a specific company?” hashtags=”AI, BigData”]

Improving performance with business intelligence

Some larger technology companies have been at the forefront of utilising this type of Q&A interaction for consumer use. Google with its search engine and more recently it’s Google Home and Amazon with its smart home device ‘Alexa’ are leaders in this area. Servers can scan through huge amounts of data almost instantly to provide information and answers to any questions consumers could conceive.

The question is, however, how can intelligent machines aid in tailoring big data for a specific company? No matter what the size of a company, whether it is big or small, local or global, the challenge for suppliers of these machines is understanding their individual ‘key performance indicators’ that are unique to each company, putting the data into a digestible form and consequently using the data to the advantage of the company in question. Companies such as NetSuite, for example, provide this service through a dashboard function in which large volumes of data can be presented in a way that supports directors and managers in running and growing the business. As soon as the data changes, the dashboard changes.

Solutions are also now coming into play that can allow multiple systems to work simultaneously together, to  avoid the disadvantages of employees manually entering information, which takes a long time and allows room for human error. Not only do systems like this increased efficiency, but they also allow for an increase in data visibility and data accuracy.

This is particularly effective when integrating cloud systems. For example, the increase in sales channels available means that even leading retailers are no longer reliant solely on their e-commerce store and use 3rd parties such as Amazon and eBay to distribute their services. The data from these systems can now be integrated with their internal business system.

The time is now

As stated previously, data and the way it is managed is becoming increasingly important for businesses to innovate and succeed in competitive environments. Many leading professionals have commented that they believe 2017 has been the year of data analytics. Artificial intelligence is set to take the leading role away from data engineers in the management and control of data, automating processes and as previously mentioned reducing human inaccuracies and speeding up processes.
Gartner recently produced a report looking at the future of data analytics showing how organisations are already innovating their systems to keep up with competitors by encompassing the entire business in their approach to data analytics. The report also suggested that the majority of businesses have not got the systems currently in place to support ‘end-to-end architecture built for agility, scale and experimentation’.

Going forward, the report suggests that data analytics will not simply reflect the performance of business, but also drive modern business operations. Executives should begin to make data and analytics part of the business strategy, which will allow data and analytics professionals to assume new roles and create business growth. These changes will drive the use of data and analytics.

Although, completely AI managed systems may be further off than we think, businesses should be looking at utilising semi-automated machine intelligence to deliver the business intelligence they need in understandable data chunks to become more efficient, profitable and plan for the eventuality of improving their systems in the future.

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