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CostPerform’s multidimensional costing function leads to improved profitability

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Brian Plowman
Brian Plowman

CostPerform's new multidimensional costing function allows users to analyze large datasets of sales transactions containing multiple dimensions like product, customer, country, etc. The function automatically imports transaction data, updates cost models for each dimension value, then allocates costs to individual transactions based on drivers. This provides a more accurate view of profitability across dimensions compared to traditional single-dimension costing. The analysis of over 100 million transactions showed the function can efficiently handle "Big Data" volumes and store detailed cost and margin results for each transaction in the database for analysis in tools like QlikView.

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Why multidimensional? Traditional costing models are mostly based on a single dimension output like ‘products’ or ‘customers’. Because of this single dimensionality, some cost allocations might not reflect a true cause and effect relation to the output and can lead to wrong decisions. A traditional example is the cost of the sales force. If the cost model contains only one dimension, say product, you might want to allocate sales force costs as an overhead to all products based on say sales value; or worse on the costs of each product. This can lead to high cost products being ‘over-priced’ where perhaps the sales force actually spends more time on less costly products. This ‘cross subsidising’ effect can lead to wrong decisions. Of course cost of a product is hardly ever the real driver for sales costs so in a multidimensional approach you analyse what a sales force does. It spends time and money on existing clients, on specific sales channels or countries and perhaps also on specific products such as a marketing campaign. In order to prevent cross subsidising you want to allocate costs with the right ‘driver’ to the right ‘dimension’. In an example from a Telecoms business the time spent on the UK market was first allocated to the object ‘UK market’. Next the costs were allocated to those transactions that occurred in the UK, based on the best available driver, say sales volume. The same sales department also incurred costs on a world wide marketing campaign for ‘Smart phones’. In the multidimensional cost model these costs were first allocated to the object ‘Smart phones’ of dimension ‘Product group’ and then to only those transactions that involved smart phones. So instead of allocating sales costs with one driver two steps were used as well as better drivers to the transactions. This resulted in a more accurate cost allocation with less cross subsidising. Why transaction based? Sales transactions or order lines are facts. The more facts in your cost model the better accepted are the results of the calculations which get used to improve decision making. The transaction files are the life blood of the organisation containing valuable dimension information that is easy to obtain to update the model at any time. Data mining: better decisions. Once the allocations to the transactions are done, the user can analyse the ‘result cube’ in many ways using all dimensions, driver values and cost-per-dimension result fields. Interactive slicing and dicing of the result cube leads to a better understanding of the true causes of profit and loss from the multidimensional perspective. The output is automatically generated as a pivot table within Costperform or can be analysed via OLAP tools such as QlikView. #1: CostPerform’s multidimensional costing function leads to improved profitability CostPerform has a great new function to handle large data sets of sales transactions or order lines. In many organizations, these types of transaction files are not only easily available but they also contain valuable cost driver information for analyzing multiple ‘dimensions’ such as Product, Customer, Sales channel, Country and so forth. With this function you can pull or push costs via these dimensions to the most granular level available - your individual transactions. The flexible pivot function within CostPerform runs on the ‘result cubes’ so you can slice and dice to explore the true profitability from the multidimensional perspective. Better information for better performance improvement decisions. How does it work? Via a scheduled task this function is designed to work automatically to:  Import transactions, update attributes definitions and values.  Calculate and update the cost model for each dimension instance found in the transaction file. CostPerform’s USP CostPerform is not competing with Big Data analysis tools that are designed to find hidden relationships in existing mountains of data. CostPerform delivers a new piece of ‘calculated’ information that is missing from the data. CostPerform provides profitability information at the detailed granularity level found in the transaction data. This new insight into true profitability from multidimensional perspectives leads to better decisions about where to focus on improving profitability. Traditional one dimensional costing methods are no longer fit-for-purpose. For today’s more rigorous needs CostPerform does the job……and more. The new multidimensional functionality in Costperform can take data feeds directly from your transaction files and is also the ideal partner to work hand in hand with all the leading edge Big Data tools so that ‘profitability’ could be one of the most valuable pieces of information added to the data set. Conclusion. If you want to know the true cause of profit & loss then simply feed your transactions into CostPerform, run the model and start slicing and dicing on all dimensions until you find the right areas to improve your profitability. Info: +44 (0)3 303 305 307 www.costperform.co.uk enquiries@costperform.co.uk Example pivot table: Margin by Country, Channel, Customer Group
How it works The Meta model contains a special layer called Transaction layer. This special layer cannot contain objects but knows where it’s ‘objects’ (transactions) are stored. Transactions are never loaded into memory. If a model contains a transaction layer the calculation starts to process the related transaction table. As a result, all members of each dimension are inputted or updated into the cost model as an object in a layer designated as the ‘Dimension layer’. For all selected values in the transaction table, the calculation sums each value per member of each dimension. These values are stored per object in (generated) attributes and can be used as a cost or distribution driver. Once the driver values are updated, the cost model is calculated. The end user has to make sure the allocations or (preferably) distribution to the members of the dimensions are defined. For all dimension members that receive cost, the calculator distributes the costs for each member from each dimension to the transactions using any available driver. As a result, each transaction contains costs-per-dimension results as well as total costs and margin. The transaction import task takes care of:  Creating the transaction table  Importing the transactions  Updating the meta model attributes  Updating the cost model for each dimension member found in the transaction table. Handling Big Data files The capacity to process transactions is only limited by time and database capacity. We’ve tested the multidimensional function with a transaction file of 100,000,000 lines containing the data describing:  4 dimensions (product, client, channel and country)  3 cost driver values (number of products, income and weight) In just over 2 hours on a SQL server database the update process performed the following steps:  100,000,000 lines were imported into a CostPerform database table.  Per each of the 4 dimensions, 3 values were summed for each member of each dimension. This resulted in 3 x 4 =12 queries  Each unique occurrence within each dimension (all product ids, client id etc) was inserted as object or updated in the target CostPerform cost model.  The cost model was calculated  The results per transaction were stored in the database table.  Each transaction contains the original transaction and the result-set  The result set consists of the ‘Cost per dimension’, a total cost value and a margin value  In total 600,000,000 values were updated.  In total, the result-set contains 1,300,000,000 fields A big advantage of this function is that internal memory usage is stable, regardless of the number of transactions to process. #2: Putting CostPerform’s multidimensional costing function through its paces CostPerform has a great new function to handle large data sets of sales transactions or order lines. These days the sheer volume of transactions in the business would be part of the data set that is now called ‘Big Data’. In many organisations, this type of ‘transaction file’ is not only easily available but also contains valuable driver information (volumes, sales value…) and multiple ‘dimensions’ such as Product, Customer, Sales channel, Country of sale and so forth. With the ‘transaction layer’ option added to a model, CostPerform can access the Big Data in the company and auto-update cost models straight from the transactions and calculate the latest costs per dimension, total costs and margin. The transactions are stored in the CostPerform database, ready to be analysed in the pivot function and be picked up by any OLAP tool for analysis. This multidimensional costing approach is very well suited for organisations that want to:  understand true costs and profitability on the highest possible level of granularity;  auto-update their cost models by transactions and have year to date cost information in order to make better operational improvement decisions. Info: +44 (0)3 303 305 307 www.costperform.co.uk enquiries@costperform.co.uk Analysing 1,300M results A result-set of 1,300M fields requires specialised OLAP tools. For example using QlikView on top of the result-set gave the following satisfactory outcomes:  Loading and compressing took 45 minutes  Opening without re-compressing took only 30 seconds  Slicing and dicing, selecting and clicking with almost no delay Example QlikView multidimensional analysis

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CostPerform’s multidimensional costing function leads to improved profitability

  • 1. Why multidimensional? Traditional costing models are mostly based on a single dimension output like ‘products’ or ‘customers’. Because of this single dimensionality, some cost allocations might not reflect a true cause and effect relation to the output and can lead to wrong decisions. A traditional example is the cost of the sales force. If the cost model contains only one dimension, say product, you might want to allocate sales force costs as an overhead to all products based on say sales value; or worse on the costs of each product. This can lead to high cost products being ‘over-priced’ where perhaps the sales force actually spends more time on less costly products. This ‘cross subsidising’ effect can lead to wrong decisions. Of course cost of a product is hardly ever the real driver for sales costs so in a multidimensional approach you analyse what a sales force does. It spends time and money on existing clients, on specific sales channels or countries and perhaps also on specific products such as a marketing campaign. In order to prevent cross subsidising you want to allocate costs with the right ‘driver’ to the right ‘dimension’. In an example from a Telecoms business the time spent on the UK market was first allocated to the object ‘UK market’. Next the costs were allocated to those transactions that occurred in the UK, based on the best available driver, say sales volume. The same sales department also incurred costs on a world wide marketing campaign for ‘Smart phones’. In the multidimensional cost model these costs were first allocated to the object ‘Smart phones’ of dimension ‘Product group’ and then to only those transactions that involved smart phones. So instead of allocating sales costs with one driver two steps were used as well as better drivers to the transactions. This resulted in a more accurate cost allocation with less cross subsidising. Why transaction based? Sales transactions or order lines are facts. The more facts in your cost model the better accepted are the results of the calculations which get used to improve decision making. The transaction files are the life blood of the organisation containing valuable dimension information that is easy to obtain to update the model at any time. Data mining: better decisions. Once the allocations to the transactions are done, the user can analyse the ‘result cube’ in many ways using all dimensions, driver values and cost-per-dimension result fields. Interactive slicing and dicing of the result cube leads to a better understanding of the true causes of profit and loss from the multidimensional perspective. The output is automatically generated as a pivot table within Costperform or can be analysed via OLAP tools such as QlikView. #1: CostPerform’s multidimensional costing function leads to improved profitability CostPerform has a great new function to handle large data sets of sales transactions or order lines. In many organizations, these types of transaction files are not only easily available but they also contain valuable cost driver information for analyzing multiple ‘dimensions’ such as Product, Customer, Sales channel, Country and so forth. With this function you can pull or push costs via these dimensions to the most granular level available - your individual transactions. The flexible pivot function within CostPerform runs on the ‘result cubes’ so you can slice and dice to explore the true profitability from the multidimensional perspective. Better information for better performance improvement decisions. How does it work? Via a scheduled task this function is designed to work automatically to:  Import transactions, update attributes definitions and values.  Calculate and update the cost model for each dimension instance found in the transaction file. CostPerform’s USP CostPerform is not competing with Big Data analysis tools that are designed to find hidden relationships in existing mountains of data. CostPerform delivers a new piece of ‘calculated’ information that is missing from the data. CostPerform provides profitability information at the detailed granularity level found in the transaction data. This new insight into true profitability from multidimensional perspectives leads to better decisions about where to focus on improving profitability. Traditional one dimensional costing methods are no longer fit-for-purpose. For today’s more rigorous needs CostPerform does the job……and more. The new multidimensional functionality in Costperform can take data feeds directly from your transaction files and is also the ideal partner to work hand in hand with all the leading edge Big Data tools so that ‘profitability’ could be one of the most valuable pieces of information added to the data set. Conclusion. If you want to know the true cause of profit & loss then simply feed your transactions into CostPerform, run the model and start slicing and dicing on all dimensions until you find the right areas to improve your profitability. Info: +44 (0)3 303 305 307 www.costperform.co.uk enquiries@costperform.co.uk Example pivot table: Margin by Country, Channel, Customer Group
  • 2. How it works The Meta model contains a special layer called Transaction layer. This special layer cannot contain objects but knows where it’s ‘objects’ (transactions) are stored. Transactions are never loaded into memory. If a model contains a transaction layer the calculation starts to process the related transaction table. As a result, all members of each dimension are inputted or updated into the cost model as an object in a layer designated as the ‘Dimension layer’. For all selected values in the transaction table, the calculation sums each value per member of each dimension. These values are stored per object in (generated) attributes and can be used as a cost or distribution driver. Once the driver values are updated, the cost model is calculated. The end user has to make sure the allocations or (preferably) distribution to the members of the dimensions are defined. For all dimension members that receive cost, the calculator distributes the costs for each member from each dimension to the transactions using any available driver. As a result, each transaction contains costs-per-dimension results as well as total costs and margin. The transaction import task takes care of:  Creating the transaction table  Importing the transactions  Updating the meta model attributes  Updating the cost model for each dimension member found in the transaction table. Handling Big Data files The capacity to process transactions is only limited by time and database capacity. We’ve tested the multidimensional function with a transaction file of 100,000,000 lines containing the data describing:  4 dimensions (product, client, channel and country)  3 cost driver values (number of products, income and weight) In just over 2 hours on a SQL server database the update process performed the following steps:  100,000,000 lines were imported into a CostPerform database table.  Per each of the 4 dimensions, 3 values were summed for each member of each dimension. This resulted in 3 x 4 =12 queries  Each unique occurrence within each dimension (all product ids, client id etc) was inserted as object or updated in the target CostPerform cost model.  The cost model was calculated  The results per transaction were stored in the database table.  Each transaction contains the original transaction and the result-set  The result set consists of the ‘Cost per dimension’, a total cost value and a margin value  In total 600,000,000 values were updated.  In total, the result-set contains 1,300,000,000 fields A big advantage of this function is that internal memory usage is stable, regardless of the number of transactions to process. #2: Putting CostPerform’s multidimensional costing function through its paces CostPerform has a great new function to handle large data sets of sales transactions or order lines. These days the sheer volume of transactions in the business would be part of the data set that is now called ‘Big Data’. In many organisations, this type of ‘transaction file’ is not only easily available but also contains valuable driver information (volumes, sales value…) and multiple ‘dimensions’ such as Product, Customer, Sales channel, Country of sale and so forth. With the ‘transaction layer’ option added to a model, CostPerform can access the Big Data in the company and auto-update cost models straight from the transactions and calculate the latest costs per dimension, total costs and margin. The transactions are stored in the CostPerform database, ready to be analysed in the pivot function and be picked up by any OLAP tool for analysis. This multidimensional costing approach is very well suited for organisations that want to:  understand true costs and profitability on the highest possible level of granularity;  auto-update their cost models by transactions and have year to date cost information in order to make better operational improvement decisions. Info: +44 (0)3 303 305 307 www.costperform.co.uk enquiries@costperform.co.uk Analysing 1,300M results A result-set of 1,300M fields requires specialised OLAP tools. For example using QlikView on top of the result-set gave the following satisfactory outcomes:  Loading and compressing took 45 minutes  Opening without re-compressing took only 30 seconds  Slicing and dicing, selecting and clicking with almost no delay Example QlikView multidimensional analysis