THE DATA DOWNLOAD

 This is part one in a two-part series, focusing on creating actionable KPIs and goals for compelling dashboards. If you’re interested in reading the second part of the series, check out “You Don’t Have to Be a Rocket Scientist to Be a Data Scientist.”

It’s no secret that business analytics and reporting are milestones in the road to success. Analytics and Key Performance Indicators (KPIs) have become strategic assets to businesses and critical to decision-making. And the trend is only growing. Gartner forecasts that the worldwide business intelligence (BI) and analytics market will reach $16.9 Billion in 2016 (Gartner, 2016).

With the growing demand, it’s time to evaluate your organization’s current BI system. Does your company use traditional BI systems that deliver analysis by way of reports? If so, you may have a problem. The problem is what started with such enthusiasm (“Dozens of reports are sent weekly!”) has turned into a lament (“Dozens of reports are sent weekly.”). They are the same words but different sentiment. If you find that you belong to the latter group, you need to ask yourself, “Are these reports just historical trends and yesterday’s data?” If yes, you may be in trouble.

You have a data warehouse up and running, and your analysts are building reports and dashboards, containing actionable data about your business and customers. But are you missing a large piece of the puzzle?

We all know that listening to what customers are saying on social media is a critical component to a company’s marketing plan, not to mention its overall business strategy. This level of customer engagement goes beyond monitoring customer loyalty programs, surveys, and tracking customer lifetime value metrics. Leading organizations need the ability to leverage social media analytics to raise brand awareness and enhance customer service.

One of the principles behind the Agile Manifesto states:

The best architectures, requirements and designs emerge from self-organizing teams.

This is a key success factor in agile data management, whether the team is developing a traditional data warehouse or any other type of enterprise data management solution. 

Self-managing teams can be very effective due to the following factors:

• Better, faster communication.
• More trust between client and product team.
• Less conflict.
• Increased motivation.
• Informed decision-making.