Analysing future sales (A Level) flashcards

Topic 10: Analysing future sales

Three period moving average: how it is calculated and where it is placed

(period 1 + period 2 + period 3) ÷ 3, placed against the middle period. Slide the window on one period and repeat. Number of moving averages = number of data periods − 2.

Weekly orders: 620, 710, 680, 770, 800. Calculate the three period moving averages.

Week 2: 2,010 ÷ 3 = 670. Week 3: 2,160 ÷ 3 = 720. Week 4: 2,250 ÷ 3 = 750. The raw data fell in week 3, but the trend is upward.

Forecasting from moving averages: method (moving averages 670, 720, 750 placed at weeks 2–4; forecast week 6)

Average change = (last MA − first MA) ÷ (number of MAs − 1) = (750 − 670) ÷ 2 = 40. Forecast = last MA + (periods ahead × average change). Week 6 is 2 periods after week 4: 750 + 80 = 830.

Forecast error: formula and example (forecast 450 units, actual sales 414)

Forecast error (%) = (actual − forecast) ÷ forecast × 100. (414 − 450) ÷ 450 × 100 = −8%: sales were below forecast.

Extrapolation: meaning and value

Extending a past trend into the future, assuming the pattern continues. Quick, cheap and objective; useful short term in a stable market. But blind to new rivals, recessions and shifts in taste, less reliable further ahead, and weak for new products.

Qualitative forecasting methods

Expert opinion; the Delphi technique (an anonymous expert panel answering in rounds until views converge); sales force composite (each salesperson estimates their area and the estimates are totalled); hunch or intuition.

Qualitative forecasting: advantages and disadvantages

Advantages: works with no past data (new products, start-ups), can anticipate changes, uses staff knowledge of customers. Disadvantages: subjective and open to bias (staff on targets may forecast low), hard to check, formal panels take time and money.

Difficulties of sales forecasting

Changes in the external environment, competitor moves, one-off events (weather, supply problems, publicity), no data for new products or markets, longer horizons and wider error, and bias or gaps in data.

Impact of sales forecasts on decisions by function

Operations: capacity, scheduling, inventory, supplier orders. HR: recruitment, training, overtime, temporary staff. Finance: budgets, cash flow forecasts, external finance. Marketing: promotion, pricing, distribution.

Over-forecasting vs under-forecasting

Over-forecasting leaves surplus stock (raising storage costs and tying up cash) and idle staff. Under-forecasting leads to lost sales and stockouts.