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Assignment 1

Page history last edited by /pd 5 months, 2 weeks ago

Question 1

Consider a working environment. It could be your current organization, an organization where you have previously worked, or a fictional organization. Think about the role of technology in the organization and how it assists managers and other employees with efficiency and productivity. 

Now, think about the strategies the organization is currently pursuing. Does the organization rely on cost leadership, differentiation, or focus? How might AI technologies contribute to (or be inconsistent with) these strategies? Which strategy would you choose to emphasize in your chosen organization? How could AI potentially fit in with the strategy you have chosen? Are you able to use any of these three strategies to innovate in ways that may bring new value to the organization?

Using the questions above to guide your thinking, write a report of between 300 and 500 words detailing the current state of your chosen organization. Your report should include a section detailing how AI (or other technologies) is currently being deployed in the organization, as well as a section that outlines the organization’s strategies. Ensure that your writing is coherent and clear.


My Organization is a leader in the mobility and logistics  market space.  We are constantly striving to use technologies across all business units, to gain efficiencies ,  innovate,   enhance our talent capital and grow the bottom line.  To met our objectives there is a big push to DISCOVER, DIGITIZE AND DISRUPT using AI  technologies like Machine Learning, Robotics, Deep Learning, Predictive analytics , Robotic Process automation platforms and such tools and methods.   The overall execution of the digitization strategy resides under the CIO/CDO  portfolio. To this end we have dedicated teams for driving innovations, testing new concepts in the Enterprise Lab or working with Startup's to pilot emergent technologies.   


The team is always striving to provide the highest quality products at the most optimal price, i.e driving cost leadership, Focus and Differentiation.  I have chosen the  below business cases to outline our current capabilities in the overall strategy implementation.


Cost leadership 

In Germany in collaboration with a research center, our organization  has created and implemented a virtual reality game to train employees on processes within a  warehouse.  This will slowly get rolled out to all our facilities  and employees of a warehouse.Thus saving in training costs and lowering the total cost of ownership.



The  Lego  65 feet high Cathedral /Warehouse  in  Germany is one  most complicated pieces of automation and  robots in warehouse operations. The whole warehouse is one big automated process with  hardly any human operating other then the gatekeepers who monitor the whole operation.  The  warehouse process manages  , a total 65.6 square-miles of shelf space-900 million pieces at any given time.   This is engineered with the focus on a single customer's business needs.  


In summary, there are multiple initiatives that are being piloted or already implemented.    The organization has a strong sense of direction to utilize AI , Robots  and machines to execute and create  on emergent trends. 



In a pilot process,  robots were used in a warehouse to automate regular order /demand fulliments. This speeding up the  overall process and freeing employees time to do other more complex tasks.  


he robots are being piloted in DB Schenker's Leipzig warehouse, to automate tasks associated with regular order fulfillment, speeding it up and allowing employees to focus on more complex tasks



Tariff classification is a process that is done by humans.  This is a core business process for imports/customs brokerage operations.  The government needs an importer/broker to assign a  tariff number to all items being imported that dictates how mach duty and taxes need to be paid to the government. We are currently training a machine to use historical data for items that are in "akin" status and automatically assign a tariff# to the new item.  The algorithms / proof concept based on a hybrid of  background nets  with additional deep sets of  proprietary  inference rules. The goal is to gain  operational efficiencies and lower Total Cost of Operations.


Currently working with a partner on Predicate Analysis and inventory management for  a High Tech leader in hardware.  Inventory is needed  at various sites to ensure obligation  to demand fulfillment are met.   Any discrete or unplanned   events happening in the supply chain has an impact  to delivery obligations and  booked revenue.   The algorithms are harvesting  big data  from flight data,  geospatial data (IoT) and weather conditions  at origin, in transit and destination stations.  Thereby predicating if the shipment is within or out of  the set key boundary indicators.   This allows the partner to take a proactive business decisions. e.g. contingency pull from other sites/hubs etc. Thus helping to negate disruption  within the  partner's business.  The model is based on reinforced learning that enables partner to sustain excellent market leadership. We intend to roll out to other partner once we reach MVP status.










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