How to get your BI, Data and Analytics working in harmony?

If you clicked on this article, I am guessing you have at least one of the following challenges:

• Your team doesn't have the dashboards to do their job effectively: They may have tons of dashboards (or none at all) but, regardless, they lack actionable metrics to do their job
• Your data structure is holding you back: You know the problems but getting them fixed is organizationally impossible
• Your team can't agree on definitions: You frequently spend time in meetings clarifying definitions rather than making decisions

If any of these problems sound familiar, odds are your Business Intelligence, Data and Analytics are not working in harmony. From experience there are seven layers in the data analytics pyramid (see image at top of article for an illustration):

• Prescriptive Analytics: Can you guide the actions to take based on data?
• Predictive Analytics: Can you forecast the future?
• Performance Management: Do you know how the team is doing against goals?
• Operational Reporting: Does the team know if they are winning?
• Data Quality: Does the team (and your automations) keep the data accurate?
• Data Architecture: Do fields capture the right data and relate logically to each other?
• Infrastructure: Do you have the right systems to handle your data and are they plugged in correctly?

While most understand this data pyramid well, I still see many companies experiencing the challenges described at the beginning of this article. The fundamental challenge they face is that the layers don't work together to drive success. Below we highlight the interconnected nature of the layers of the pyramid.

To get your data, BI and analytics efforts working in partnership, here are a few best practices I have learned from experience:

• Have documented definitions: Without this foundation it is hard to ramp new people and ensure consistency.
• Clarify BI responsibility: Often I see analytics teams focused on powerpoint presentations and operations teams focused on data. What suffers is BI. To fix this make sure you consciously resource for and define ownership for BI, otherwise your teams will suffer.
• Have a single team own all three layers: Tying the data, operational reporting and analytics together ensures all three functions work closely together towards a shared goal of amplifying the company. This is the approach we have taken within our Customer Group at Culture Amp. We then partner with product analytics and finance to leverage data across the company.

The challenges of data and analysis aren't easy but hopefully this structure and ideas inspire you. I would love to hear your perspective in the comments section!