14 Questions You Should Ask Before Diving into Your Business Intelligence & Data Analytics Project
Business intelligence and data analytics technology have made some impressive advancements over the past few years. Nowadays, businesses of all sizes can get into the analytics game by leveraging easy-to-use dashboards to access data with greater speed, ease, and understanding than ever before. This represents a huge opportunity for organizations to increase revenue and improve operational efficiency in ways that weren’t possible just a few years ago.
Despite an abundance of exceptional tools and expertise available to leverage analytics, getting these projects off the ground remains a challenge for many organizations. According to Gartner, more than half of all analytics projects end with unsatisfactory results because they aren’t completed on time, within budget, or they fail to meet the requirements of the business.
Given the sheer breadth of options coupled with the complexity and scale of your growing database, it’s easy to point the finger at the design and implementation of the solution. However, the root cause of the problem rarely occurs in this phase. The success of a project is determined long before a line of code is ever even written.
Before you dive into any reporting and analytics project, a fundamental, clear, documented understanding of the business goals and expected results is critical to ensuring all business requirements are met in the new solution. To help avoid ambiguity or design assumption that occur mid-project (leading to more time and money spent on reworking the solution) we’ve gathered a list of key questions to ask before development begins.
Goals and Objectives
- What problem/pain point are you intending to address?
- How will you define success?
- How much is it worth to solve the problem?
- How will you confirm a ROI is achieved?
Data Integration and Aggregation
- Where is the data?
- What known data gaps exist?
- How are disparate data sources associated with one another?
- What business rules (logic, math, exclusion, etc.) must be applied to support the desired solution?
- What hypothesis exist about the answers you hope to obtain from the desired solution?
Reporting and Visualizations
- What reports exists in the absence of the desired solution, and how are they created?
- What questions can’t you answer easily today that should be answered by the solution?
- When you analyze data in existing reports or raw form, what KPIs or thresholds are you reviewing?
- What actions are you trying to drive from the report/visualization?
- Who are the report audiences and how are their needs different?
If you’re looking for a strategic partner who can guide you through the steps to a successful business intelligence and data analytics solution, contact SWC to learn more.
Download our guide, The Essential Guide to Data-Driven Decision Making, to explore real-world examples of how modern organizations are overcoming the barriers to becoming a data-driven business and how you can be leveraging data analytics to grow.