Understanding which technologies are appropriate for your business, and how to make good technology buying decisions can be a real challenge. This is where WF&FSA’s Technology Insights comes in. Supported by WF&FSA’s Technology Committee, this site offers advice, insights, updates and suggestions to help you make the best technology investments, while addressing questions that often that cause confusion.
Click a link, below, to see the related articles and information, and add your comments at the bottom of each article. Let your opinion or ideas be heard! Here's where you'll get the latest technology information and ideas, tailored to your business needs. Selected content will also be published in the monthly WF&FSA netWORK e-newsletter.
Bob DeStefano of SVM E-Business Solutions presented a powerful workshop at WF&FSA's 2012 Conference. Here are some valuable Tech Tips from Bob:
WF&FSA Data Exchange Standards
SAVE TIME, SAVE $
WF&FSA has addressed the ever increasing demand for seamless transfer of data and product information by developing the WF&FSA Data Exchange Standards. Please read the information below to understand the power that this tool can provide to your company, and view the items on the right for further details.
The WF&FSA Data Exchange Standards is the road map we have created to carry the vehicle, in this case XML (Extensible Markup Language) to transfer all of the information on any specific product that may be required for the ultimate use in marketing distribution and data capture of that SKU.
- One roadmap
- One language
- One Vehicle
- One consistent set of rules for all commodities
- One program
Why consider using the Standards? The Vendors perspective…
- Discipline having all information a Wholesale/Distributer would ever require available in 1 file
- Eliminate data entry errors for your customer
- Vendor only required to do the work once
- One program communicates with multiple wholesalers
Why consider using it? Wholesale Distributor perspective…
- All information that could ever be required from a vendor is presented in 1 download.
- Save time updating existing items
- Save money
- Eliminate Data entry errors
- Avoid duplication
- Update 1 vendors files in a single pass
- One program communicates with multiple vendors
WHAT IS XML?
Extensible Markup Language (XML) was first brought into the spotlight in 1996 by the World Wide Web Consortium (WC3). XML is a markup language just like HTML, but without the fixed format. A markup language provides words and tags that describe a document and identify the pieces.
While HTML is about presentation, XML works to store and transport structured data. All XML files follow some basic rules for syntax and form. The simplicity of the language allows the author to develop a structure that focuses on the data with customized element tags. XML improves the functionality of the Internet by providing files that are flexible and adaptable.
XML is a simple language that most anyone can master. It does not carry the same rules and strict syntax that other Internet languages require. This makes it a good choice for novices and experts alike. Once you have the basic rules down pat, creating a well-formed XML file will provide a straightforward way to organize, transmit and update data.
SIMPLE XML EXAMPLE
FIVE REASONS TO USE XML
Simplicity – XML is easy to understand. You create the tags and overall set up of your document. What could be simpler than that? When writing a page in XML, the element tags are your own creation. You are free to develop the system based on your needs.
Organization – XML allows you to build your platform by segmenting the design process. Data sits on one page, and formatting rules stay on another. If you have a general idea of what information you need to produce, you can write the data page first then work on the design. XML allows you to produce the site in stages and stay organized in the process.
Accessibility – With XML you compartmentalize your work. Separating data makes it accessible when changes are needed. When time comes to change an inventory record or update your details, with XML, separating data makes changes easy and time-saving.
Standardization – XML is an international standard. This means that anyone in the world is likely to have the ability to view your document. Whether you are sending data to users in Alabama or Timbuktu, chances are they can to access the data. XML puts the world in your virtual backyard.
Multiple Applications – You can make one data page and use it over and over again. This means if you are cataloging inventory, you only do it once. The end user can create as many different displays of the information as they want for that data. XML allows you to generate different styles and formats based on one page of information.
Ultimately, XML is a tool. It keeps your design work organized into practical compartments. The easy nature of the language doesn’t require massive amounts of knowledge or an alphabet behind your name. XML saves time and keeps the design flow organized. When you think about it, why wouldn‚t you use XML?
Data mining can be defined as the process of sorting through large quantities of data to identify patterns and trends. These patterns and trends can be collected, analyzed and used to make intelligent decisions pertaining to specific business scenarios, such as:
- Forecasting sales
- Determining what products might be sold together
- Targeting sales mailings towards specific customers
- Predicting customer buying trends
- Identify faltering customer sales
Creating a data mining model is a dynamic and repetitive process. It involves asking questions to define specific goals, gathering data to create an output model to answer those questions and using the model to deploy meaningful reports into the working environment.
The first step in the data mining process is to define the business problem or need as specifically and clearly as possible. To successfully complete this first step, questions such as the following might need to be answered.
- What similarities are you trying to find?
- Are you trying to forecast sales?
- Are you looking for seasonal trends?
- Are you trying to recover lost sales?
The answers to these types of questions and the needs of the individual business users have to be analyzed and compared to the available data. If the current dataset does not support the needs, the data mining project will need to be redefined. It is important that all individuals involved from management to the end users take part. While upper management might have a solid understanding of the business needs, the end users will be the ones actually working with the data model output and will need to have a solid understanding of the final goals to be achieved using the model.
Organizing The Data
The next step in the data mining process is to gather, consolidate and clean the available data. If the data is stored in multiple locations, it would be best to centralize it on one machine. Depending on the rules established for data entry and how strictly they are enforced, incorrect, missing or inconsistent data entries may be present in the data. The following are a few examples that can cause data filtering problems.
- Missing or incomplete data entries
- Inaccurate pieces of data.
- Data entries varying between upper case, lower case or mixed case.
- Similar types of data that are both abbreviated and full length.
These data anomalies will need to be cleaned up before any type of accurate reporting can be performed. Furthermore, data cleanup might need to go beyond missing or inconsistent entries. There are other aspects of the data will also need to be researched.
- Data Classification Level
Should the output model be based on “Order Date” or “Ship Date”? Do you rely on “Net Price”, “Gross Price” or ”Discounted Price”? Is there clear and accurate data classification levels defined and how are the levels set up? Do you want see sales by “Customer Location” or “Warehouse Location”? Are sales totals to reflect “Assigned Salesperson” or “Sold By Salesperson”? These examples along with numerous others will need to be analyzed in order to determine what data is best to use for the output model.
Exploring Your Data
The third step in the data mining process is to explore the prepared data. A complete understanding of the data and knowledge of what to look for is vitally important to make intelligent decisions when creating the mining output models. You will need to determine the dataset’s accuracy and establish that it can provide the necessary results. By performing some basic calculations on the prepared data values, it will be possible to tell if the data is skewed, inaccurate or possibly incomplete.
- Minimum Value Calculations.
- Maximum Value Calculations.
- Average Value Calculations.
- Standard Deviation Calculations.
By incorporating the above calculations into you data exploration, deviations or variances can be observed. If there are significant deviations within the values, the need for more data might be necessary in order to provide more balance throughout the dataset. If the data proves to be accurate, there might be problems with inaccurate business expectations. As a result of exploring your data, understanding it and knowing what to look out for, decisions can be made on whether or not the data is flawed. If the data is flawed, a plan can be conceived on how to fix the problems. If the data is accurate, a greater understanding of trends within the business can be attained and the data mining plan can be modified to represent these new understandings.
Create Final Reports
The final step in the process is to generate clear and meaningful data reports which display the answers to the business problems or needs defined in the first step of the data mining process. Whether you are using a powerful business intelligence software package such as IBM Cognos, or a program already included with Microsoft Office like Excel, it does not make any difference. What matters most is that the final reports be laid out in a manner that is easily understandable for all individuals using them. The information and knowledge attained from these reports can be both invaluable and endless.
- Sales history reports can inform of customers who once were high volume buyers and sales have diminished over the years.
- Along with the customer sales history, a sales potential can be incorporated into the report to show which customers would be most beneficial to go after.
- An item classification sales report might show customers that purchase a specific product class from you, but sales of associated item classes are nonexistent.
Importing report information into a mapping program is another way to use your data output.
- Customer locations can be pinpointed and this might show where to concentrate your sales force in order to build up customer base within a specific region.
- Delivery routes can be laid out more efficiently directly on a map and potential customers that are skipped over within a route can be observed.
Sometimes a picture can be worth a thousand words. These are only a few examples of what you can do with a clean, well organized, accurate data set. The possibilities are virtually endless and the power within the data can be invaluable.