Using Data To Be Smarter

6th September 2019

Various projects and operations fail due to the lack of sufficient amount and good enough data. Poor decisions lead to poor outcomes and these are usually made based on “gut feel” and emotions. Often today, gathering data isn’t the problem as we seem to be generating way more than we know what to do with through standard day to day operating alone. The challenge is to analyse the data, put it into context and be data-driven when making decisions. Today, it is people who are employed to gather, analyse and present information in ways which mean something.

Although the talented individuals who can interpret data in those ways are fantastic to have, highly competitive businesses implement Artificial Intelligence embedded within a data analytics software which does the pattern recognition and interpretation for them. This then allows the people to get smarter with the data, make strategic decisions their competitors aren’t expecting, putting the business ahead of others.

“Getting smarter with the use of data” doesn’t necessarily mean that anybody is learning, it does, however, guarantee that decision making is much more reliable due to the larger amount of data supporting it.

Companies such as Starbucks use their own data analytics software to decide where to open up their new branches. The program takes into account customer demographics, behaviours, traffic and location to suggest where to open up the next branch. This way, Starbucks can open multiple branches within very close proximity and still have each one profit highly! Another great example is Amazon. This company uses AI to improve customer relationships and boost marketing by taking your data, learning about what you like most and plugging adverts in wherever they can to get you to buy from their site.

Understanding these opportunities, Manufactory focused heavily on developing and incorporating Artificial Intelligence into its software package to help and extract meaning from data generated in a process. 

Good AI-driven software can help with questions such as:

  • What is happening in the business?
  • Why is that happening?
  • What is likely to happen?
  • What can we do in advance?

Businesses can benefit from analytics tools which segregate irrelevant data and group the ‘good’ sets. These can help to highlight real root causes of pain points and suggest actions to recover from them. Additionally, having the ability to look at historical data sets can enable businesses to predict potential outcomes, prepare for them and ultimately have a strong competitive advantage in the market.


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