Data Culture Matters (part 2)

Data Culture Matters (part 2)

4. Data Champions and Culture Catalysts

If your efforts to create a rich data culture are going to be successful – identifying, recruiting, and partnering with enthusiastic data champions within the organization is an absolute must. C-Suite mission statements and company-wide initiatives that are as disruptive as digital transformation require catalysts at each level of the business to bridge long-term vision with front-line execution and adoption. This means educating and empowering middle management and the leaders of specific business units to lead the charge. The best culture catalysts will be business leaders and their ability to sell the value of analytics to their respective teams. Knowledge workers on the front-line live and breathe their daily work. Business leaders can articulate the impact data and analytics will have on daily decision making in the language of their unit and drive adoption – a process which is essential to securing top-down dedication to change. When looking at the current state of data literacy and analytics adoption within the organization you might feel that some groups are not yet advanced enough for increased access to business intelligence. You may be correct that data literacy levels are not at ideal levels, however, you can’t learn to read if you don’t have a book! Creating curated analytics experiences with varying amounts of business intelligence for different groups and roles is a great way to slowly increase access to data and drive data literacy over time. Data literacy will be crucial in every role within the next few years, so there is no better time to start than now.

5. Uniting Talent and Culture
 
The competition for data talent is fierce and growing, and as a result new roles and titles are emerging within the business. In the Higher Education space during 2018, CDO was more likely to mean Chief Diversity Officer than it was Chief Data Officer. However, things are changing, and they are changing fast across all industry verticals – take for example the evolution of the Data Scientist function. How does this effect culture? Given the growing need for data talent across all industries, it is now less important to hire from within your industry as you traditionally might for management, marketing, and sales roles. When it comes to emerging data talent, it is more important to find great talent that fits within the company culture of change and innovation – regardless of industry. Additionally, a diverse range of perspectives on how to extract value from data and analytics will add value to business outcomes and will help push the momentum of change within the organization.


6. Data Culture, Risk, and Ethics

The last topic we will discuss is the necessity to address risk and ethics in your data culture. Data management is increasingly important, including the ability to understand who, how, and what data people are using to make decisions. Misuse of data can institutionalize unfair biases like racism and sexism. Audit capabilities are increasingly important and valuable in understanding what data and reports are being used to make decisions.

Data culture is essential to driving the initial and continued success of BI and Analytics initiatives. No matter what stage of analytics maturity your organization is at, remember that it is important to identify daily decisions that can be influenced first, continue to educate the c-suite on the value of business intelligence, provide easy access to BI for everyone, recruit the leaders of business units to drive front-line adoption, hire great talent and include diverse perspectives, and maintain and unbiased and ethical approach to data use.

For more information on driving data decision making, read this article on BI-Modal Analytics

Data Culture Matters (part 2)

Data Culture Matters (part 1)

Gartner currently covers over 250 analytics vendors in their research. By the time you are done reading this article, I wouldn’t be surprised if there were two new vendors or tools. With the recent explosion of business intelligence and analytics tools on the market, you might find yourself drowning in a (data lake) of information and possibilities. What visualization tools should we use? Am I ready to pursue predictive analytics? Who should be using these tools? Whether your company is at the beginning of its analytics journey or operating at the bleeding edge of technology and strategy, one common theme will always be important – culture and mindset. A lack of organizational buy-in can hinder even the most well designed, thoroughly vetted analytics strategy. When it comes to data culture here are 6 essential topics to consider:

1. Data Culture is Decision Culture

Data culture may be experimental – but the objective is always to make better business decisions. Collecting data for data’s sake is useless. A great place to begin leveraging analytics is where people are already making decisions. Communicate with the leaders of specific business units and determine what critical information they use to make daily decisions. To go a step further, consolidate this information in a curated analytics experience for each department, group, or role. Once these groups begin leveraging the unique analytics relevant to their most common decisions, they will become curious what other insights they can discover. To continually improve the value of analytics, it is important to implement an effective feedback loop between business end-users and report developers. Report-rating and commentary mechanisms are critical capabilities necessary for feedback and communication between users and developers to improve the quality, scope, and impact of informational assets.

2. Data Culture and the C-Suite

There isn’t an executive you will meet today who would admit that data is not a priority in their decision-making process, but many don’t actually have a comprehensive understanding of how analytics can benefit the larger organization. Often times it is difficult for executives to define valuable problems for the analytics team to solve. Find ways for your analytics team to engage with and educate the C-Suite so that leadership understands the value behind the entire organization using analytics. A great way to demonstrate this value is by delivering a complete view of the business to your executives via a personalized business intelligence command center. Consolidate the most important KPI’s, reports, and visualizations from various tools and systems in a single pane of glass for quick, effective, executive decision making.

3. The Democratization of Data

The first step when trying to generate organizational excitement about using data for decision making is to simply get analytics in front of different groups within your organization. The informational assets available now, your reports and visualizations, might not be perfect yet – but the sooner you make them available, the sooner you can improve them. By presenting analytics to your end-users regardless of your analytics maturity, you expose them to the power of data-driven decision making, and before you know it, they will be asking for more. This is crucial in securing the organizational buy-in required for the additional investments in business intelligence that you need. One of the most effective ways to increase analytics adoption is to remove the barriers to access, and put analytics in front of your end-users through an easy to use, single point of entry for all the analytics assets you provide.

Check back after the holidays for 3 additional areas of focus when building a strong Data Culture within your organization.