A retail company deployed an ML model that predicts weekly product demand. After six months in production, the operations team notices the model's forecasts are becoming increasingly inaccurate, even though the model code has not changed. Customer buying patterns have shifted due to new competitors entering the market. Which phase of the ML development lifecycle should the team focus on to address this problem?