Smarten:: Helping Businesses Leapfrog to Augmented Analytics
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Most organizations are at different levels in their journey of analytics, and most of these journeys began with comparison year on year or month on month sales and profit. Some moved on to comparing market shares and budgeting using past data and trends. We were all a part of this journey either using a spreadsheet or a report.Visualization was the biggest leap which put Business Intelligence platforms in front of many eyes. Clicking and filtering graphs and drilling down data based on a hierarchy became more critical and useful. Smarten, developed by India based Analytics company is one of the few companies with an analytics platform which has been built from the ground up in Asia. It is also one of the first platforms which will get users to leapfrog to Augmented Analytics.
Smarten has chosen to differentiate itself with a single point or maybe a dual point push at the users. While the company has a complete traditional and as well as modern Business Analytics platform, Smarten is focused on Self Service Data Preparation with Assisted Predictive Modelling. This allows the preparation of data and advanced analytics without writing code or SQL.
So how does Smarten work and what extraordinary value it will provide the users is the question we asked this company. Kartik Patel, the Founder and CEO of the organization shared his views that Smarten, which is mentioned in multiple reports by Gartner has always been focused on deep analytics and it is because of this that they are leading the way into augmented analytics. He said, “At the moment we may not be the best in dazzling you with some unique graphs, but if you want to do clustering without any special skills, we are the tool to choose.”
Look at a typical situation where one has a 100,000 to spend on sales promotion, and you want to select the most suitable outlet out of 2500 retail outlets which sell your product which would sell most of the product you have in excess stock.
Any user can run a clustering analysis through Smarten while preparing data with great ease in Smarten’s Self Service Data preparation platform.
Some of the most common scenarios in which the users can use Smarten effectively without any expert as per the team are:
• Consolidating disconnected data, like macro-economic data from the internet, data from a market survey and sales form the ERP to provide insight into the impact of macro-economic data on the business and market share.
• Effect of business variables like vacancy, stock levels, new competition, logistics and delivery time and even the education level of the workforce on the profit of the organization can be worked out using a regression model.
• A retail store manager can cluster his 10,000 SKU to find out which products are best moving for the diverse range of festivals in some countries or can determine which products sell together for proper shelf placement.
• With the selection of algorithm automatic for predictive analytics, users can make decisions based on data rather than sheer guess work. If you reach out to this company with a case where an end-user has an advanced analytics problem which he wants to solve on Smarten, the users get a special discount; a bit more than what the IT department would have negotiated. Smarten is set to put predictive analytics and advanced analytics in the hands of all!
“At the moment we may not be the best in dazzling you with some unique graphs, but if you want to do clustering without any special skills, we are the tool to choose”
Some of the most common scenarios in which the users can use Smarten effectively without any expert as per the team are:
• Consolidating disconnected data, like macro-economic data from the internet, data from a market survey and sales form the ERP to provide insight into the impact of macro-economic data on the business and market share.
• Effect of business variables like vacancy, stock levels, new competition, logistics and delivery time and even the education level of the workforce on the profit of the organization can be worked out using a regression model.
• A retail store manager can cluster his 10,000 SKU to find out which products are best moving for the diverse range of festivals in some countries or can determine which products sell together for proper shelf placement.
• With the selection of algorithm automatic for predictive analytics, users can make decisions based on data rather than sheer guess work. If you reach out to this company with a case where an end-user has an advanced analytics problem which he wants to solve on Smarten, the users get a special discount; a bit more than what the IT department would have negotiated. Smarten is set to put predictive analytics and advanced analytics in the hands of all!
