Building Intelligent systems The mjunction way

Sweeping Mega Trends Data in Our Lives IOTS AI Automation FB Almost 1 M Logins , 4,50,000 Tweets , 156 M Emails & 15 M Texts every MINUTE Big Data Growing at 40 % Annually IOTS 75 Billion Connected Devices in 2 Years time AI Programs for Facial Recognition, Analyzing Social Media , Listening Automation Machines taking over the 4 Ds – Dull , Dangerous , Dirty and Dear

Sweeping Mega Trends Robots 2020 Global Personal Robots Market estimated at 17 Billion Assisted Living , Household Care Products , Teaching Assistants , Companions ( Nannies , Personal Assistants Steep Fall in Pricing from 1,50,000 USD to < 1000 USD

Top Emerging Industries 2020 Virtual Commerce 3 D Big Data Logistics Cyber Security Cloud Compute Growth Potential Managed Services Wellness Market Size

The Challenges facing the corporates Today How much should I produce given a set of constraints ?( Production capacity, profit margins volatile prices ) How do I know what my dealer will purchase next month and the month after that and what quantity , which SKU etc ? Can I Know How will my customers respond to any Stimuli before doing the activity How much Inventory should I order given the Production target and the default tendencies of vendors ? Can I Know beforehand which of my customers are going to churn The Challenges facing the corporates Today

Can An Intelligent system Tell me all of these at the click of a Button ? Yes all of these are possible and mjunction addressing these issues by designing intelligent systems

How do we use Intelligent Systems to benefit our Customers 150 + forward Auctions of secondary steel alone , around 100 reverse Auctions per day of various materials How do I estimate the prices that these auctions would throw up ? How do I contact the right Bidder for the Right Auction ? Machine learning systems which would learn from each auctions, take in external factors and recommend us: The most likely set of bidders for an Auction, the opportunity for cross selling. The Prices that might result from an Auction. A centralized data warehousing system repository of data to make data available across categories across clients- To make better price forecasting and better buyer/seller recommendations possible

Automated Systems in Supply Chain for Better Decision making Balance higher Inventory holding vs loss of production on account of shortages . Automatically raising of P.O’s based on shortages and future demands. Vendor default predictions to optimize Inventory holding costs. Price Planning – Automated price recommenders - increase/decrease in demand ML Systems to predict shortages in stock /going out of stock( Finished Goods) ML Systems to  recommend products in excess and automatically reduce price to clear inventory. Past buying patters by customers ML Systems for Fraud detections/Exception Analytics

ML Based Fraud Detections Systems Finding application in various Industries like retail, banking, FMCG, manufacturing etc Bidder Collusions in procurement process Identification of Fictitious Vendor Submission of fake Invoices Inflation in procurement prices Misreporting of sales- channel stuffing Fudging book of accounts

Changing paradigms of Channel Engagement Heavily reliant on human and the knowledge that they bring in to Manually estimate the expected sales Conceptualize activities which would bring in the results in terms of promotions, schemes and other marketing spends Primarily a one scheme fit all method for promotions Ready Informations about the channel propensity to respond to any promotional Activity ML Algorithms to predict churn tendency even for the channel Ability to forecast sales down to the SKU levels for each channel partner. Intelligent systems to cluster the channel partners as per their expected behavior.

THANK YOU By: Dipankar Mukherjee mjunction services limited