Business Intelligence
Our EPOS systems link in to a Data-warehouse which keeps a full history of your transactions. From this data-warehouse we build a Business Intelligence (BI) Cube. You can access this Cube via Microsoft Excel or via our BI web portal.
Benefits of BI
The benefit of using business intelligence can be summarized as giving you speedy, customizable, analytical and powerful access to your business data. In order to run a business effectively managers need insights in all kinds of key business data, such as detailed sales information and sales performance. The challenge is getting key data out of the vast pool of information and then presenting it so that key strategic and tactical decisions can be made.
If you have worked with BI before then the benefits will be known. If you are new to BI then a summary of the benefits is:
· Consistent view or "unique truth". One source of data enables all parties in the organization to base their information on a "unique truth" and not from disparate, often independent and in some cases inaccurate personal summaries of key business data held in spreadsheets and other formats.
· Easy access to data. Improved information dissemination, improved information access and propagation of knowledge about the organization, monitoring of key business indicators and extremely fast monitoring.
· Easy analysis and reporting on a host of aspects of underlying business with instant views of performance.
· More effective and efficient business process management, planning and anticipation of business trends
· Better use of time. With more data available automatically there is less time required to build and collate information required by the company.
· Freeing up human resources by using the most expensive resources to apply their time improving business not gathering data, and allowing greater satisfaction for employees over their work
What is BI?
Technically the BI starts with a data-warehouse of all of your transactional information, so each transaction (date time, store, clerk, products, price etc..) is stored in the data-warehouse. From this data-warehouse we build cubes of information - a cube is a simple way of visualizing the data, in reality is it multi-dimensional.
So for example; if you imagine a cube with date, store, product representing the axis or sides of the cube. Then at each cross reference in the cube we store the values for that combination; so Store A on 10-2-2009 for product = Latte sold 10 items. This information is presented much quicker since the cube, and hence all the sums and calculations, is pre-processed at night and allows dynamic analysis. The cube "knows" how many Lattes sold on each day for each store, as well as how many for each month for each store, etc..
Give me an example?
Example 1 - present clear weekly summary information to store managers. This can be done via the web interface.
Example 2 - Review an advertising campaign
For our example we have a company COFFEE CO that sells Coffee and Sandwiches, they have decided to run a local advertising campaign across three stores offering a new range of sandwiches as a special deal "coffee and new sandwich", now that the campaign has been running a week they wish to review how the project is working.
Traditionally this would require someone to run the reports from each day listing the sales of products and then to take the key numbers from these reports and enter them in to a spreadsheet, by gathering this information day by day and re-keying it they will get an analysis, but this takes time and effort and also allows for human error. Once the spreadsheet is done they can e-mail it around the company, but then this has to be re-done each week when new data is added. To add to the complexity they want the information by store and they only want the manager of each store to see their own data, so the person preparing this information has to create separate spreadsheets to send to each manager, more time and more effort.
With the BI solution a single spreadsheet is created which contains a pivot table liked to the cube. The operator can drag from the list of data "store name" to the rows, filter by the stores they want, drag the Date to the columns then drag the Net Sales in to the cells and you instantly have Net Sales by store by Site by Date. Finally drag the Product Group next to site and filter this by Sandwiches, New Sandwiches and Coffee. Now you have net sales by each key product group, by site, by date - your analysis is done.
This can now be sent to everyone in the organization, or loaded on to the portal for remote access via a browser. Since the data will be refreshed each day, you need do no more design, every time you open the spreadsheet you have the most recent data. Also since each user has to "logon" to access the data the data is filtered for their security settings, the spreadsheet will only show each user the information they are allowed to see. Job done!
What else can we do?
The data cube contains alot of information based on EPOS activity and can be expanded to bring in information from other sources. For example the cube contains:
· Sales data: Net Sales, Gross Sales, Customer Count, Tax
· Product Sales: Net Sales, Gross Sales, Qty
· Basket analysis: which products sold with other products
· Payment Methods:
· Sale Type: Refunds and exchanges
· Price Levels:
· Clerks:
· Locations, Sites and Companies
· Products and product groups
· Forecasting
· Fiscal Calendar and standard calendar, this year, last year comparisons
· KPIs: Key Performance Indicators
· and more....
In addition to the basic information we can customise solutions to include data from other sources and build and mange your own portal to contain operational information and even work flow anaysis. There is so much more to BI than can be communicated in this web-site, so please call us to find out more. |