Many organizations use a combination of business tools to manage their sales, marketing, finance, and HR operations. Digital transformation is accelerating faster than ever in the business landscape.
Most of these tools have a reporting module which displays data and statements specific to each department.
But, data such as sales figures, lead numbers and email open rates can only give you so much information about customer behavior.
Businesses are increasingly digitally driven and digitally-driven. It is crucial that they include a comprehensive business intelligence program as part of their technology strategy.
Comprehensive business intelligence programs combine data from many sources and perform cross-functional analyses to uncover intuitive insights such as inspirations behind seasonal customer patterns, reasons for supply chain gaps, sales funnel pain points gathered through customer feedback, productivity drops caused by employee attrition and future trends.
This information is powerful and can help organizations adopt a culture that supports smart, evidence-based decision making.
Get started with business intelligence and analytics
Once your company has the resources and funding to implement a central program of business intelligence, it is time to start identifying the key business metrics that you would like to track and compute.
As here has already pointed out, the next step in defining your data strategy is to identify the goals.
First, you need to define your data strategy for key areas. Next, identify and align data sources with this strategy.
It should then be easy for an organization to create a data pipeline, and prepare data for analysis.
A robust and unified data pipeline is built from disparate sources
Organizations face one of the most difficult challenges when implementing business intelligence programs.
Mixing toolsets from different vendors can lead to dissimilar data sets. These data sets need to be first merged, blended, and unified to allow for a smoother, more accurate analysis.
It’s been noted, that 80 percent of analysis time is spent preparing data. Poor quality data can often lead to untrustworthy business insight.
These are where BI tools with data preparation provisions can be of great assistance. It doesn’t matter if you are building a business intelligence program from scratch or creating a custom tool, data-prepping and data blending capabilities are essential. This means that the option can connect to multiple sources (legacy and cloud apps), and allow data to be exported in different formats. You can also clean up duplicates and merge the data into one data warehouse.
This ensures reliable business intelligence and robust data pipelines that are error-free.
Update your privacy practices and policy
Your obligation to protect customer data is greater when you have a BI program. Keep these privacy tips in mind:
- Masking of critical user data: i.e., removing personally identifiable data from all data sets using anonymization methods before they are fed into the BI data pipeline
- To use anonymized data in BI analysis, it is necessary to obtain explicit consent from customers and employees.
- Also, ensure that all data sources are subject to strict privacy standards.
Integration of your BI program and internal collaboration platforms
Many organizations have difficulty achieving adoption and prompt decision-making, despite having a comprehensive, expensive BI program.
This can be solved by integrating the BI system across all internal communication and collaboration platforms, such as chat, email, and intranet forums, and project management avenues.
The BI dashboards should allow executives to visually blend data and create cross-functional insights. They can then make the insights into interactive reports that are easy to understand and share with the relevant teams and individuals in real time.
Future-ready, but still open to innovation
You can implement new technologies to improve your operational efficiency and run a future-ready company by being open to innovation and adapting to change.
Your BI program should also allow for experimentation and take advantage of emerging opportunities such as AI-powered voice analysis and RPA/business analytic integration.
Current AI trends allow users to have conversations with AI assistants and generate automated BI insights in a click. They can also predict future trends, perform cognitive and what-if analysis, and more.
The past two years have shown us that things can change quickly, and it is important to be flexible.
Cloud-based BI tools allow business owners to view real-time data across multiple departments. to make quick decisions. This allows businesses to be agile in unprecedented times.