The Lifecycle of Implementing A Holistic BI Solution
Congratulations! You are one of thousands of companies that just bought a brand new business intelligence tool. Now that you are part of an elite group, what do you do exactly with your new BI tool? Unfortunately, you and I aren’t the only ones asking this question.
Organizations are keen to resolve one of the most painful challenges of having a unified repository of analytics and reporting. The hype behind out-of-the-box BI tool capabilities and promise can be overly exaggerated and neglects the huge amount of expensive work, time and resources needed to successfully implement them.
The objective of this article is to simplify the understanding of the evolution of BI towards a true, unified solution and increase the awareness of the required process, costs and alternatives. However, before we delve into the next evolution of BI, let’s briefly discuss the meaning of business intelligence.
What is Business Intelligence (BI)?
According to Gartner, business intelligence (BI) is a term that includes a number of broad functions – applications, technologies, architectures and tools, and best practices that provide access to and transform raw data into useful information for improved business performance.
It all starts with raw data. That said, data is just data – a binary flow of details that has no standalone meaning.
Step 1: Infrastructure – The First Step towards BI
To enable having a BI Solution, the first step is to build a BI infrastructure.
A BI infrastructure (e.g., data warehouse, data mart) is a separate and independent IT-related environment. It contains a huge set of IT processes and development parts that extract data from internal sources (such as the sales force automation system) and external data sources (such as IMS or specialty Pharmacies) into one, unified repository.
In order to address business questions and uncover business insights into specific topics, the data should be processed to match the relevant business unit needs. These requirements need to be determined up front, as the infrastructure is being designed and built.
This initial phase is complex and required, yet the data is still raw and not truly usable. The next step is to transform the raw data into meaningful data sets that make sense to the business. This can be tricky because it should imitate the logic, the working procedures and methodologies that are in place within your business unit.
Step 2: The BI tool – Enabling the Infrastructure
A BI tool is the generic, development tool that provides the presentation layer that displays BI data to the user, ready for analysis. The tool provides functionality and visualization to easily slice and dice the data in a variety of ways and also display the output via charts, graphs and dashboards.
Step 3: BI Solution – The Next Evolution in BI
A BI solution is an analytical application that has been developed using the BI tool based on the BI infrastructure data. It’s highly tailored to meet the business’s (e.g., commercial operations) analytics needs.
Developing the solution requires a strong understanding of the business logic, methodologies and end-user processes, in addition to common industry standards and techniques.
For example, in the Pharma industry, the solution requires understanding the various data sets, metrics, user systems (CRM) and processes, such as pre-call planning, which are utilized.
Furthermore, the solution should also take into consideration the variety of roles and responsibilities in order personalize the BI solution to each user’s needs, such as a sales rep or home office analyst.
Step 4: The BI Solution Roadmap
The hope is that the business intelligence tool that you purchased would provide you with a holistic solution, efficiently piecing together data and allowing you time to focus on what brings value to your business. However, acquiring a BI tool is only the first mile on the road of having a BI solution in place.
The average development duration of such project is 12-18 months from definition to delivery. Let’s take a look at the key actions and implications of implementing a BI solution.
Actions and Implications of BI Solution Implementation
Step 5: Building a Better BI Solution
The long process detailed above can be significantly shortened by using a preconfigured, SaaS solution that is specific to verticals in the industry. This solution has significant advantages over the “traditional” process.
- Pre-built – While still configurable, best practices (such as data model, ETL’s, BI infrastructure) and KPIs are already designed from the start, leading to a much shorter average implementation time of three months to deployment.
- Deep Domain Expertise – The solution is already road-tested by users within the industry and the solution is supported by industry experts.
- Software-as-a-Service – Being cloud-based and agile means user change requests take hours, not weeks. And so, there is no need to worry about BI infrastructure concerns
- Lower Total Cost of Ownership – No need to learn, build and maintain a solution from scratch
Certainly, purchasing a BI tool may seem like the best option for your business objectives, but it is the first milestone of a long and costly development journey. As IT is faced with the challenge of developing a robust and multi-utilized business intelligence solution from scratch every time, adopting a pre-configured Pharma BI solution is favorable. Benefit from integration of different Pharma needs and Pharma executives insights; save on costs; cut training hours with ease-of use; and easily accommodate dynamic market changes.
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