Porteolas - Agility for what's next

CASE STUDIES

Below is a sampling of various operations challenges I’ve experienced thus far – not an exhaustive list, a high-level representation of approaching qualifying & quantifying common challenges – experienced by most (if not all).

Operations’ Financial Insights

1) Challenge:

**ADDING NEW PRODUCTS** :: A manufacturer of home exercise equipment has introduced two new weight machines at a trade show.

2) Constructs & Constraints:

Dealer's order far exceeds current manufacturing capabilities. For each of the two new machines, you're given:

(1) Raw material costs for each component, (2) For each stage of manufacturing: # hrs available, # of laborers & their wage, (3) Production of machine-2 be at least 25% of total production, (4) Dealer's 30% discount on purchase price, and (5) Assumption: 100% of production sells

3) Approach:

Use linear programming to explore the region of feasibility & determine the optimal unit production of the two machines that maximizes profitability, filling as many orders as possible.

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1) Challenge:

**MEET STAFFING REQUIREMENTS** :: Due to a potential merger, the company is looking to augment their current staff with temps for the duration of their operations (est ~ 6mo).

2) Constructs & Constraints:

There are three contract options available to choose from and two training options to choose from.

(1) The temp gets to choose their availability, (2) No temp can be contracted past the anticipated merger date, and (3) Meet staffing demands while minimizing the combined costs [contract + training]

3) Approach:

Once the costs and options have been tabled, apply linear programming such as Microsoft Excel's solver function to generate some recommended solutions for meeting staffing needs while minimizing expenses incurred.

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Supply Chain Tactics

1) Challenge:

**DISTRIBUTION CENTERS** :: A manufacturer and distributor of meters, has decided to address the efficiency of their distribution system - better meet customer demands while minimizing costs.

2) Exploring Options:

(1) Reduce current distribution center limitations, (2) Satisfy some of the demand directly from production plants, and (3) Impacts on capacity from future growth

3) Approach:

Using network models methodology, evaluate the options they're exploring to determine the cost saving of each &/or their combination; make recommendations.

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1) Challenge:

**FORECAST FOOD & BEVERAGE SALES**:: Owner-operator of a local restaurant wants to remain high-quality while continuing to grow. She would like a forecasting model built for her to implement.

2) Constructs & Constraints:

She currently has three years of operations data. She wants to monitor and project seasonality of sales - at a minimum of one year out.

3) Approach:

Incorporate forecasting methodologies to include: annual moving average and centered moving average (reduce error in forecasts), seasonal irregularities (reveal potential deviations).

Establish a seasonal index, then apply to both historic and forecasted data. Including weighted moving averages puts more weight on recent data and less on older data. Lastly deseasonalize your values and forecasts to establish seasonal forecasting.

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Market Research & Analytics

1) Challenge:

**PROMOTIONAL MEDIA MIX** :: A golf association must decide on the best mix (TV, streaming radio, social media) for promoting their upcoming tournament.

2) Constructs & Constraints:

The committee has four goals w/n three priority levels: (1) Reach at least four million people, (2a) At least 30% TV, (2b) No more than 20% radio, & (3) Adhere to allotted budget

3) Approach:

Using multi-criterion methodology, run scenarios for each of the three priority levels - capturing the pros/cons of each for advising on best compromise.

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1) Challenge:

**OUTFITTING a 7-PIECE RECORDING STUDIO** :: For staff & faculty use in creating & providing online content

2) Constructs & Constraints:

Neither the studio, nor the equipment are line-items on the operational budget; depending on donations to cover costs.

3) Approach:

Complete a multi-criterion matrix for each of the 7 components' (price, reviews/ratings, compatibility, technical specs, & vendors). Identify best function & value for complete studio. Submit request for funding / donation.

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Location & Workforce

1) Challenge:

**EMPLOYEE AVAILABILITY** :: A textbook publisher looks to maximize total unit sales volume; they must decide which books to publish.

2) Constructs & Constraints:

Given: (1) the projected sales of ten textbooks, (2) three employees for the project, and (3) the annual publication constraints imposed by management.

3) Approach:

Using integer programming, run scenarios varying employees' availabilities - solving for the maximum unit sales volume achievable, while adhering to managerial constraints.

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1) Challenge:

**PURCHASE & DEVELOP LAND** :: A condominium developer is aware of a foreclosed property that may be a good buy, to develop. Should they participate in the bidding, or not?

2) Constructs & Constraints:

Two major factors come into play

(FIRST) The potential to be highest bidder: (a) bidding requires a deposit equal to 10% the value of your bid and (b) Winning bid recoups that 10% as a 'deposit', losing bids forfeit their 10% as 'fee to participate'

(SECOND) The potential to [not] get the required referendum changing the zoning: (a) The property is currently zoned for single-family homes and (b) Losing would result in owning a non-productive asset

3) Approach:

*BE RESOURCEFUL*:: (1) Gather data from previous studies, (2) Run some preliminary analyses - probabilities of being high-bidder & rezoning approval, and (3) Consider expensing market research services - if/when your initial efforts indicate 'favorable' chances.

*EVALUATE PROBABILITIES*:: (1) Best case, favorable chances and (2) Potentials for sunk costs -- [a] 10% fee, [b] the expense to consult market research service and/or [c] win the bid, but fail to get zoning for land to be 'productive'.

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