Lynn University Forecasting & Error Analysis PK Village Case Study

Question Description

PK Village is a neighborhood 24-hour convenience store chain. The outlets, located in gas stations throughout South Florida offer over 10 thousand SKU (store keeping units), including limited selections of dairy products, packaged foods, over-the-counter medications, basic apparel, electronic accessories, hardware, tools, and automotive products.

The first store opened in 2002 and it is managed by Sammy Patel, one of its owners. The company now operates a network of 12 stores spread throughout Miami-Dade, Broward and Palm Beach counties. The partners are considering opening other branches in other parts of the state and eventually expand nationwide through franchises after 2020.

One of the products sold by PK Village is a general use lubricant sourced from a factory in Malaysia and packed under the PK Village private label.

Ms. Patel has noticed that, over the past year, the company has experienced frequent shortages of this SKU, resulting in lost sales as well as periods of excess inventory.

Ami places orders for this product every month and is considering implementing a routine methodology to estimate future demand for this product.

The demand for this SKU during the past five years is shown in the table below:

Month 2014 2015 2016 2017 2018
Jan 211 244 291 323 328
Feb 338 403 386 478 510
Mar 191 213 335 327 310
Apr 192 244 278 327 346
May 138 153 159 211 261
Jun 148 195 209 342 296
Jul 205 231 205 288 394
Aug 244 327 364 374 331
Sep 164 337 263 304 305
Oct 200 247 280 337 300
Nov 205 234 282 304 322
Dec 229 438 273 357 369

Ms. Patel has retained your services to recommend a forecasting methodology to estimate the demand of generic lubricant. Your document should contain:

  1. Analysis of the historical data series, including identification of seasonality
  2. A forecasting error comparison of these methodologies:
    • Two-period moving average
    • Three-period moving average
    • Single Exponential Smoothing with constants of 0.4 and 0.3
    • Linear regression (annual) with seasonality adjustment (monthly)
  3. A summary of your recommended next steps.

Include the Excel file showing all calculations.

This short consulting report (no more than three pages long) must be written using business language.
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