Life goes on and business is constantly moving forward. New clients come, new services appear, personnel are employed and tasks change. All these developments are displayed not only in documents, reports and final results of the company, they are subject to serious adjustments in installed business systems, like bi tools, financial analysis software, manufacturing planning software, resource planning software and others.
In fact, corporate budgeting tools or production planning software are always constructed on the basis of metadata, like data directories. All manufactured products or services are categorized into more general groups. For example, workers are attributed to teams, then workshops and production plants. Stores can be categorized into a chain: area-region-country. To read how the automation of strategic planning was carried out by Spreadym, inc in a Grocery Retailer follow the link.
The data categorization within an enterprise can be more complex and look like a matrix. For example, equipment can be categorized not only by workshops and production plants, but its description can also be supplemented by capacity volume and manufactured assortment. Such cross-detailing is important when you need to calculate a monthly production plan and debottleneck production lines. For the record, low capacity utilization rate is often the cause of weak production performance.
If we add financial indicators to operational data, such as cost and revenue items per product category and a production unit, then we will get not just a matrix at all, but a multidimensional data model. To effectively manage this multidimensional data model, metadata (or data directories) must be centralized. For example, working in a classic Excel file, a user must not only change the category in the data directory, but also check all dependent models for adaptation of these changes. We do not want to pay a lot of attention to the risks of such a manual approach (for example, errors, missed formulas and items), but we all perfectly understand that they are hard to escape.
The solution to this problem of data preparation and processing is the centralization of metadata updating and the automatic distribution of changes through all dependent models in one planning and analysis software for business. In addition, an extra bonus to it may be the unification of financial models for all database users (for instance, in this case, depreciation won’t be charged in the middle of anywhere). In Spreadym, a platform for financial analysis and operational planning, we not only set up centralized management of metadata and financial and operational models through Excel, but also split access to confidential data into such units so that the owner of administrative rights could draw the boundaries for users as accurately as possible. One can be given access only to specific rows of data, another person can have access to the metadata of a certain segment and so on. You can read more about granular security here.
The data categorization within an enterprise can be more complex and look like a matrix. For example, equipment can be categorized not only by workshops and production plants, but its description can also be supplemented by capacity volume and manufactured assortment. Such cross-detailing is important when you need to calculate a monthly production plan and debottleneck production lines. For the record, low capacity utilization rate is often the cause of weak production performance.
If we add financial indicators to operational data, such as cost and revenue items per product category and a production unit, then we will get not just a matrix at all, but a multidimensional data model. To effectively manage this multidimensional data model, metadata (or data directories) must be centralized. For example, working in a classic Excel file, a user must not only change the category in the data directory, but also check all dependent models for adaptation of these changes. We do not want to pay a lot of attention to the risks of such a manual approach (for example, errors, missed formulas and items), but we all perfectly understand that they are hard to escape.
The solution to this problem of data preparation and processing is the centralization of metadata updating and the automatic distribution of changes through all dependent models in one planning and analysis software for business. In addition, an extra bonus to it may be the unification of financial models for all database users (for instance, in this case, depreciation won’t be charged in the middle of anywhere). In Spreadym, a platform for financial analysis and operational planning, we not only set up centralized management of metadata and financial and operational models through Excel, but also split access to confidential data into such units so that the owner of administrative rights could draw the boundaries for users as accurately as possible. One can be given access only to specific rows of data, another person can have access to the metadata of a certain segment and so on. You can read more about granular security here.
