Based on my experience consulting on BI/BA system development, most clients tend to look for tools first, or tools for creating or building systems, without yet having a clear system requirement. They simply want a system. If you are interested, please read on for more details
Based on my experience consulting on Business Intelligence/Business Analytics/Big Data Analytics, I've observed that many companies just starting out with projects or systems tend to look for tools first, without a clear system requirement. In reality, some companies may not need any tools at all; utilizing existing organizational tools and developing a structured system from them is far more feasible
Some organizations have a large amount of data in the form of Management Information Systems (MIS). Collecting this data in a single source and presenting it in a Business Intelligence (BI) format, utilizing existing resources first, would be more suitable and cost-effective than investing in new tools, which require training personnel and purchasing new technology
Some organizations find that they have a large amount of data but haven't yet presented it in the form of information, graphs, or reports. If this is the case, management should have their subordinates create the data into a Management Information System (MIS) first. This involves comparing targets and historical data to identify business trends. Once this data is available, developing a Business Intelligence/Business Analytics/Big Data Analytics system using various tools, including visually appealing graphs and their features and functions, will significantly reduce the time and steps involved in system development. This avoids the need to purchase tools upfront, especially when requirements are uncertain, and prevents excessive project time
5 things to consider when implementing a BI/BA/Big Data Analytics system
1. Has the data available within the organization's ERP system been transformed into information, graphs, or reports?
1.1 If you already have the data, have you compared it to historical data? If not, perhaps do so first?
1.2 If you already have the data, have you compared it to the target data? If not, perhaps do so first?
2. Management requirements
2.1 Are the requirements clearly defined?
2.2 Are the requirements constantly changing, or are they still uncertain?
2.3 How long does it take to obtain the management's requirements?
3. Management's requirements/preferences
3.1 Is data already stored in the system? Are there any guidelines
in place? 3.2 Is there someone responsible for this operation? Can someone within the organization be reassigned to this task?
3.3 Does the person responsible have the knowledge and expertise in this area? Is a consultant needed?
After obtaining the details above, we can proceed to consider the next step
4. Tools to be used to build the system
4.1 If we choose to use the tools, what features and functions do they offer?
4.2 How much budget is required for the investment, and is it worthwhile considering infrastructure, personnel, and development team costs?
5. Project implementation
5.1 There should be phases and task divisions, implemented using Agile Project Management
Nuchanat Rongrong, author of the articles
in this collection on Business Analytics.
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