Menu
-
Creating a Data Culture
The adoption of analytics across organizations is a function of the organization culture. Some companies have a strong fact-based decision-making culture. A strong evangelizer in senior management helps the cause and improves the speed of adoption.
The analytics CoE (Centre of Excellence) needs to work closely with the various functions and help in delivering value.
It is natural that some departments within the organization will be early adopters. Some functions need to be nudged. There could be a tendency for some people to resist change. Adoption is a gradual process, and it is important to show steady progress. Coming up with quick wins in highlighting the value of analytics in delivering business outcomes will help in increasing adoption.
Analytics can help in 2 ways:
Validate the “gut-feel” of the business expert Uncover new and interesting patterns that no one within the organization may be aware of Both outcomes mentioned above are useful.
A data science team will have specific goals and tasks to accomplish, but they also need a certain degree of autonomy to explore the data, and experiment with it. A culture that promotes experimentation is key to success. The engagement model between the CoE and the business teams also varies across organizations.
Analytics driving business: Consider a scenario where the analytics team is evolved but the business teams are not evolved in leveraging data for decision making. Here, you will find hyperactive analysts who “push” reports, dashboards, and other analytics output to the business teams. Business driving analytics: Consider a scenario where the business teams are mature and have a clear vision on how to leverage data for decision making. The business teams may not be experts in the algorithms, but they are clear on the output they expect and how to use the output. Business and analytics partnering: Consider a scenario where there is a healthy partnership between both the teams and each team understands and appreciates the other. As you promote cross-functionality, there will be pushback. Some departments will find the change difficult to cope and it could be disruptive to the organization.
-
The opposition could be due to various reasons:
Belief that “I know better than others” mentality If I hold on to the data without sharing with others, it will benefit me Promoting analytics leads to downsizing First let us improve the quality of our data. We can think of analytics later An organization culture plays a very important role in promoting the use of analytics. The culture sets the tone of how the various stakeholders interact with each other and how analytics is leveraged. In most cases where analytics has seen a speedy implementation, there has invariably been an evangelist at the top who has helped create a healthy culture that fosters collaboration between the teams along with effective change management.
The combination of the analytics culture, the team, and the right tools & technologies provides the difference between a good analytics team and a great analytics team. A good team in a culture that does not encourage implementation is likely to get frustrated at some point. Similarly, if any of the components is not strong, things are likely to falter at some point. In a great analytics organization, behaviours and decision-making processes are aligned to ensure that there is realization of value and ROI through analytics.
