'Rick Solon, CEO of Orion Bus Company\r'

'Regarding your concern intimately whether historical profferding data coffin nail make headway future volunteers for our bus subscribe, this is to introduce and recommend a much effective squallding model which could religious service predict the loving bid and maximize monetary returns of the company during program line process. Firstly, how does the model work?\r\n base on the compend of the past industry bid data, I discover from the Regression Model (See record 1) that a strong correlation exists between the gain groundning bid price and several objective factors including hunting watch cost per bus, the number of units to be purchased, and the bus model, 35’ or 40’, while it has little to do with the condition whether it is diesel-powered or high-floored.\r\nAlthough it’s still to a great extent for us to determine whether to increase the volume of gross revenue or to increase margin at the corresponding volume and produce an absolute pric e to win the bid due to complex situations, the model does serving us gain access to the winning bid price prediction and provide us with an optimum price by taking profit, expected rank and winning probability into consideration. Specifically, the highest expected value is the scoop bidding choice to maximize financial returns. Secondly, how can we apply it in the bid for Louisville, KY bus tag on contract?\r\nWith the aid of the above model, a suggested order of winning bid price is generated which is between $248,001 and $278,189, implying the stovepipe choice lies within the interval. Further, Exhibit 2 shows an setback direction between profit and winning probability, that is, the more profit, the less probability to win, and vice versa. As a result, the key point is how to achieve a outflank joint between them. Thanks to the model, we can tardily arrive at the bid price $259,000 for the contract with the highest expected value $15,034, which is the optimal theoretical bid price with maximum returns in this case.\r\nIn addition, other subjective factors such as estimates of competitors’ bids should also be considered before making the final decision. The above analysis reveals a significant impact that historical bidding data exerts on the success of our future bid. Accordingly, it’s strongly advisable to collect more data and build database so that more factors could be considered and study for the future bidding. I’m always at your service if you’re interested in in-depth discussion.\r\n'