What is “Agile Analytics”?
It’s a process of translating big data into insights, actions, and better decision-making to gain a competitive advantage.
In a corporate culture sense, it’s about implementing a new kind of data-focused culture across the organization while ridding your business of two increasingly common, albeit questionable habits.
First, agile analytics calls on decision-makers to slow down and ask and answer the most strategic, analytical questions about their organizations; something hard to do in today’s fast-paced, fluid business world of constant change and hasty decisions. Second, it goes against our instinct to manipulate data to fit a pre-determined idea, instead allowing data to dictate the next course or action.
As evidence of the increasing need for Agile Analytics, web searches for the term “big data” have increased more than tenfold over recent years. It’s clear that more enterprise business leaders want to leverage historically unused data to better plan, predict, and understand their businesses, which is the exact intent of Agile Analytics.
Efficient data analysis tools and more performance management systems are essential to the process. Those unwillingly to modernize their internal tools are facing a greater competitive disadvantage every day.
So if you’re looking to make better sense of their data, the following 10-step Enterprise Guide to Business Analytics will help you leverage your information to make more efficient, more well-informed decisions, while instilling a data-driven culture throughout your organization.
1. Collaborate Across the Company
Get leaders across the enterprise involved in the Agile Analytics process, particularly those in operations and finance. Gather their feedback. Invite them to test new data analysis features. What you’re actually doing is turning them into “data experts” who can help others in their department to leverage Agile Analytics and understand what moves the business forward.
2. Inform Stakeholders
Agile analytics works best when the entire organization buys-in to this data-driven culture. Educate stakeholders and encourage them to think about using analytics to evaluate their own performance and focus more time and effort on the most revenue-generating tasks. The better employees understand Agile Analytics, the more they’ll understand how their role impacts the greater business’ performance. And that sense of importance is a powerful motivator.
3. Maintain a Real-Time Performance Picture
It’s called Agile Analytics for a reason. It’s intended to help companies become more, well, agile, and quickly answer important yet unanticipated questions. It’s also agile in that the analytics are useful in several ways. They help to answer key business questions and provide the necessary data to update financial models and maintain plans, budgets, and forecasts that match the real-time realities of the business.
4. Frequently Test your Tools
Use those closest to the analytics process to regularly test your BI & CPM system and ensure they’re still producing the necessary Agile Analytics. Remember: This solution is going to be the foundation of your company’s new analytical culture. Ensure that you’ve chosen a solution that most efficiently gathers and analyzes the data that matters the most.
5. Listen to your Data
Not literally of course. Data tends to be silent. The point is that numbers don’t lie. Trust what your analytics are telling you and resist doctoring the data to satisfy your pre-determined beliefs. Adapt to the realities of your organization. Use your newfound agility to evaluate plans and forecasts and modify when necessary.
One caveat here: While numbers don’t lie, they can be misleading if you’re not measuring the most important analytics. To decide which metrics matter the most, you first have to define how to measure success.
Alleviate the maintenance burden on your IT team by automating as many processes as possible. This is why it’s important to choose an intuitive analytics solution that business users can manage. Free from their maintenance responsibilities, IT can focus their time and talents on customer-facing initiatives and other revenue-generating tasks.
7. Trust Your Self by Trusting Your Team
Trust that you’ve hired the right team of self-motivated, talented individuals who can meet your business’ high standards. Agile analytics doesn’t work in a micro-managed environment. Equip your team with Agile Analytics to help them maximize and measure they’re performance against larger business goals, and then set them free to do the job you hired them to do.
8. Incorporate (But Don’t Force) Agile Analytics
Agile analytics does not have one absolute definition. Incorporate agile methods as you see fit, and choose the systems that work best for each project.
9. Review Regularly
Agile systems provide the freedom to change course. So constantly evaluate the processes and effectiveness of your strategies.
10. Never Stop Learning
Evolve with the industry: stay up-to-date with the latest business intelligence methods and implement them into your own models. This will save later implementation hassles with your development team and keep the company ahead of competitors.