Lena is a senior manager in a software development company. She needs to make decisions for the next year pertaining to the continuation of a product that her department has worked on in the last couple of years. Unfortunately, this product has not yielded the expected revenues and clients point out problems that are hard to fix. Specifically, Lena needs to decide whether to continue investing her engineers$$ time and work in these features or stop working on this product and pursue other alternatives. She also needs to decide how much money to invest this year in the chosen project. Efforts have been invested in the current product, including hiring experts and purchasing necessary equipment. In addition, this project is in Lena$$s professional area of expertise. When she considers one of the alternatives to the existing project, she recalls the success of her company$$s competitors publicized last month when pursuing that technology. This outcome followed the competitors$$ investment of $2$ million dollars a few years ago. To provide Lena with information, her team summarized the expected short$-$term outcomes: If she switches to another project, there will be losses of $$50000$ for sure. If she keeps the current project, there is a $2/3$ probability of losing $$75,000$ and a $1/3$ probability of losing $$0.$

Based on the above information, what biases$/$heuristics might Lena have or be susceptible to when making a decision? $($Some may be in favor of one option and the others may be in favor of the other option$).$

Choose THREE relevant biases$/$heuristics that might affect Lena. Explain how each applies to Lena$$s situation.

Suggest ONE WAY to mitigate each bias$/$heuristic you described $$ a total of THREE suggestions $($could be something to implement earlier in time$).$ Explain how each suggestion is expected to help.