evidence to help the analysis would be greatly appreciated from stakeholders. The different methodologies are represented in the table below: Table 3. Methodology table for calculating annual demand for fabric treatment Methodology Calculations Detail Current Robustness? here? (1) Sales data (top Sales LOW - categories from FIRA down) Prodcom or ONS are in /Average cost of unit residual product categories, sold therefore estimating the x average metres of average cost per unit and m2 fabric used of fabric used in a residual category is likely to be = metres of treated inaccurate given the diversity fabric of products included. (2) Household metres of treated LOW/MED The major BIS – demand (bottom up) fabric in average uncertainties are on the household amount of treated fabric in the average UK home and the x no. of households average replacement rate. / average annual Therefore, likely to generate a replacement rate large range. x UK manuf. share of domestic market = metres of treated fabric (3) Company cost Cost of treating fabric MED/HIGH Company data – estimates up-rated on treatment costs is the most / market share direct way to estimate cost = cost of treating savings. Robustness will fabric improve with an increase in the market share covered by company provided data (4) Company Volume of fabric MED/HIGH - Company data volume of fabric treated on the volumes of treated estimates fabric is a direct way to / market share estimate the annual amount of = metres of treated treated fabric in the UK. fabric Robustness will improve with an increase in the market share covered by company provided data (5) Company sales Volume of in a volumes up-rated product group e.g. sofas
evidence to help the analysis would be greatly appreciated from stakeholders. The different methodologies are represented in the table below: Table 3. Methodology table for calculating annual demand for fabric treatment Methodology Calculations Detail Current Robustness? here? (1) Sales data (top down) Sales LOW - categories from Prodcom or ONS are in residual product categories, therefore estimating the average cost per unit and m2 of fabric used in a residual category is likely to be inaccurate given the diversity of products included. FIRA /Average cost of unit sold x average metres of fabric used = metres of treated fabric (2) Household demand (bottom up) metres of treated fabric in average household LOW/MED – The major uncertainties are on the amount of treated fabric in the average UK home and the average replacement rate. Therefore, likely to generate a large range. BIS x no. of households / average annual replacement rate x UK manuf. share of domestic market = metres of treated fabric (3) Company cost estimates up-rated Cost of treating fabric MED/HIGH – Company data on treatment costs is the most direct way to estimate cost savings. Robustness will improve with an increase in the market share covered by company provided data / market share = cost of treating fabric (4) Company volume of fabric estimates Volume of fabric treated MED/HIGH - Company data on the volumes of treated fabric is a direct way to estimate the annual amount of treated fabric in the UK. Robustness will improve with an increase in the market share covered by company provided data / market share = metres of treated fabric (5) Company sales volumes up-rated Volume of in a product group e.g. sofas