Five challenges faced on Small Data reporting
Big data is often touted as imperative to businesses, however in recent years perhaps we have been so blinded by Big Data that we are ignoring its poorer cousin, Small Data?
Big Data simply put looks at trends, information and patterns that can be utilised to forecast as well as give an overview of how your business is tracking. Big data takes high volumes of different sets of data and displays this information in a way that management can make decisions quickly and efficiently. Usually Big Data is generally generated outside of the business to assist the business make decisions moving forward.
Small Data on the other hand allows for the business to extract transactional information from data sources that end users can make use of immediately. Its focus is on providing information to the end user, so they can take action right now. It allows users to be able to determine why things happen, analyse this in real time and then take corrective action. Small Data can be generated as a sub set of Big Data or from other non-traditional data sources. The main thing to remember here is that it helps the end user achieve a result.
Big Data and Small Data each have their place in the business aiming to make inroads into improving decision making ability and resolve problems.
Formulating a plan to extract Small Data that suits each need within the company is paramount. If you ignore Small Data over Big Data then you are robbing yourself of some analytical tools that can help your company develop and improve.
Challenges facing managers looking at developing tools that allow Small Data reporting is:
- what type of data is required?
- where will it be obtained?
- who requires it?
- what format is it required?
- how will you extract the data?
The best methodology is to look at the problem you have and work backwards from that point.
As an example let’s look at the problem statement “Average Days Debtors take to pay have increased”. If we look at our challenge we can see that want to interrogate each customer and determine what the payments days are for each invoice payment has been made against (What). We check with accounts and find that this data can be retrieved from their SAP Accounts database (Where). It has been determined that Accounts Staff and Sales Account Managers will use the data (Who), accounts to chase up overdue accounts, and sales to check credit terms prior to selling. The decision then needs to be made as to what format they want to see the data in (What). An example may be a program that can run real time analysis of the accounting data and display that to screen. Selecting the right tool to extract and display this information is paramount to ensuring that the tool gets used (How). There are many good Business Intelligence tools that will allow quick extraction, analysis and display of the results the user requires.
As they say “look after the pennies and the pounds will look after themselves”. In other words Small Data can and will affect Big Data if looked after properly.