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Ontario Facilities Equity Management (ofem)

Essay by   •  January 21, 2018  •  Case Study  •  817 Words (4 Pages)  •  2,510 Views

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Case Analysis: Ontario Facilities Equity Management (OFEM)

The Security division of OFEM, a facilities management firm, provides security equipment and systems to its clients. Most common products include alarm and intrusion systems, security enclosures (safes), surveillance and monitoring systems, and entry security systems.

Recent developments in technology had effected both front-end and back-end elements in the security systems.

There are three technologies in which OFEM can invest in:

  • Back-end analysis – to record, analyze and interpret data from front-end technology for various purposes like security and employee monitoring
  • Front-end fingerprint recognition – can be used for all levels of security, but may be ineffective in case of individual’s skin damage or machine malfunction
  • Front-end iris recognition – relatively new technology, might falsely reject genuine users, reluctance of staff to use it

Mirella Freni, Head of Security Division at OFEM, has to decide how much to invest, and in which technology; she can also choose to invest in multiple technologies. A budget of $15m is available with the Security division, but uncertainty of revenue from each of the three options remains a deciding factor.

Options:

  • Do Nothing: Since the competitors are investing in new technology and OFEM already has set aside a budget of $15m for Security Division, doing nothing isn’t a viable option
  • Invest in all 3: Investment involved in all three technologies is huge, therefore, investing is all three might not be fruitful. Moreover, fingerprint and iris recognition and options that can replace each other, so investing in both will not benefit.
  • Invest in any 2: Due to investment amount constraints, investing in two technologies might not be a good idea. Here only viable options are to invest in Back-end plus one amongst the front-end. But due to huge costs, this option can be eliminated.
  • Invest in any 1: After evaluating the feasibility, vulnerability and acceptability of each of the three technologies, one technology can be decided:
  • Invest in Back-end analysis

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  • Invest in Front-end fingerprint recognition

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  • Invest in Front-end iris recognition

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Case Analysis: Project Orlando at Dreddo Dan’s

Project Orlando was a new product development project undertaken by PJT under its ‘Dreddo Dan’s Snacks’ brand. ‘Orlando’ was a range of snacks foods consisting of one-and-a-half inch discs of crisp, fried potato with a soft dairy cheese-like filling.

Few of the concerns regarding this new product were:

  • Ensuring product remains crisp
  • Ensuring microbiological safety
  • Capable of being stored at ambient temperature
  • Maintain physical robustness
  • Shelf life of at least three months

Key decisions regarding the development process have to be undertaken by Monica Allen, technical VP of PJT’s snack division:

  • Resources: Extra staffing would be required up to twice the current number
  • Pilot Plant: Decision regarding whether to carry-out trials in non-competitor companies or develop own pilot plant to conduct trials
  • Outsource: Due to the vast set of development activities, PJT was considering outsourcing few development activities and to hire specialist consultancies
  • Organisation & Development: Whether to create a separate department for this project, independent of the current structure

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Case Analysis: Zentrill

Zentrill, a medium-sized fashion women’s apparel retailer with 120 stores targeting relatively affluent customers between the ages of 30 and 60. The case talks about increasing the effectiveness of the whole supply chain.

Following are the three levels of the supply chain:

  • Zentrill Fashion retailer
  • Lopez Industries, a Mexico based, highly quality garment manufacturer
  • Schweabsten, a German company which manufactures cloth

Issues:

  • Zentrill: Unable to predict what the customers want, sometimes there was surplus of few items or sometimes shortages of few sizes. Failure in forecasting the volumes of each SKU results in sales loss.
  • Lopez: Unable to change the production plans at short notice. They were unable to procure extra deliveries of cloth, nor can they return any surplus to their cloth manufacturers

Options:

  • Zentrill:
  • Use data analytics to better forecast the products. Loop in Lopez and Schweabsten while forecasting in order to better inform them and minimize the bullwhip effect too.
  • Stricter norms with the supplier to improve their response rates
  • Designers can try to use similar cloth for multiple product categories this would enable Lopez to use the same raw material to manufacture higher selling items
  • Lopez:
  • Improve their response rate
  • Negotiate with Schweabsten for flexibility in supply by putting forth the high quality standard products that can be manufactured by them. Lopez can even ask for a manufacturing contract for private labels of Schweabsten

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