Advanced Analytics – Part 2
7 factors to be aware of when developing a Data Analytics or Business Intelligence solution
In a previous article, we discussed the benefits of an Analytics Business Intelligence (BI) solution. This article will be useful for understanding the factors that may lead to failure or reduce the success of an organization’s goals in developing an Analytics solution.
1. Lack of support and direction of management
For an analytics project to succeed, doesn’t only need budget sign-off and a green light from management, it needs to have objectives which align with a business strategy. They should understand the direction of the project and how it will benefit all parts of the organization. Without this support, the project could either not start, lose momentum or veer off track. Additionally, having a good project manager keeps the executive team informed and the project running smoothly.
2. The project duration is too long.
Many organizations start a BI project with a wide scope and using a waterfall development approach which can cause the timeline to belong and drawn out. Keeping your business stakeholders engaged during this time can be a challenge between capturing requirements and delivering something of value. A better approach is to adopt an agile approach, dividing the project into several phases and multiple deliverables which can help maintain engagement from stakeholders throughout the development lifecycle.
3. Data Visualization without a clear direction, story, or solution
Reports and dashboards solutions should focus on real business use cases as opposed to just providing ambiguous data visualizations. An effective solution should be able to tell a story and give you a clear idea of where improvements are needed.
4. Excessive or unnecessary reports and KPIs
It is a common problem in developing data analytics or BI solutions when end-users are creating reports, to try to cover all business cases resulting in excessive reports or KPIs.
Reports should be developed based on real-world use cases, which can be later improved, or additional reports added along with other interesting KPIs as most tools can easily support adjustments.
5. Improper tools or technology
The capability and usability of technology and tools for data analytics or BI solutions are one of the key factors in the success or failure of project development. Because choosing and developing a system based on technology or tools that are not suitable may create limitations in the future or not support the needs of the business, for example:
- The in-flexibility of on-premises systems does not support increasing data volumes and computing needs and becomes costly, complex and time-consuming to expand or optimize the whole system.
- Where the tools limitations are inconsistent with the organization's long-term analytics and data usage goals. This can lead to a higher investment than necessary, or the redundant work required to optimize the tool. For example, if the current tools do not support advanced analytics or machine learning, which requires either the migration of the analytics solution to a new system or further investment in additional tools before it can be fully utilized.
6. Poor quality data
Data is the foundation of everything and if your data is flawed, users lose trust in the solution, even though the technology isn’t the issue but the poor data that’s contained within it. Data owners and should be consulted and proper cleansing strategies applied to ensure the accuracy of the data.
Here are some examples of factors that may affect the quality of data requests
- Lack of cleansing standards and incorrect or inconsistent date types or formats from each source.
The process of importing and transforming the data is incorrect.
Lack of data validation process.
Changes in source systems impacting the data without communication between data owners and developers.
7. Lack of user acceptance/adoption
An important part of developing Data analytics or BI solutions is understanding the end-users needs and problems. Oftentimes, users are only involved after the development of the analytics solution or is nearing completion, but the results don't meet the user's needs. Which can lead to a redundant solution or a system that is not accepted by the users, leading to further development time.
The 7 factors that we mentioned above are some of the issues that can block or hinder the success of a typical data analytics or BI solution development project.
If you are interested in advanced data analytics or have questions about developing either the readiness, process, or technology/tools, please feel free to contact us for a free consultation by filling out the information below or contact us directly at +66 (0) 2 117 4344.