As businesses around the globe strive to make more effective use of data, analytics, and AI. The majority of them are still held back by a huge obstacle. There is a lack of culture that values data and analytics and it’s workable to create a data-driven culture and accumulate the competitive benefits that result.
Data-Driven Decision Making
Companies with strong data-driven decision making generally get their critical decisions through data and analytics. While a digital-native company, Amazon has a strong digital culture. There are still many traditional companies struggling to develop. This is due to a few undertaking initiatives trying to accomplish the desire culture change. Thus, it’s not surprising, in the 2019 Deloitte survey of U.S. executives share, 63% of respondents were ambiguous that their companies were analytics-driven while 67% said they didn’t prefer accessing data from their tools or resources.
CEO Role In Decision Making
The culture depends on the orientation of senior leaders, especially the CEO. There is almost no doubt that a CEO’s lack thereof in decision making and refining the business delivers a strong message to the rest of the organization. Nonetheless, a CEO’s lack of awareness doesn’t always mean that the organization can’t grow at all. Since CEOs are usually counseled on their leadership skills, they can switch to the data domain via coaching. It can be either by an internal champion or an outside expert. Moreover, Connecting data and analytics to subjects the CEO already dote on such as employee empowerment can prove effective, as can targeting outside issues that have decision-making based on data like regulatory requirements or the risk of more data-driven competitors.
While the CEO needs to become a perceptible champion of the new culture. They need an operational partner i.e. the chief data officer. The CDO is becoming the data and insight change agent.
See how CEOs could use data analytics for predictions and make decisions?
Data-Driven Culture Change Programs
Apart from trying to convert a reluctant CEO. There are three types of change programs that can take an organization in the right direction.
Educational Programs
Educational programs should be part of the initial level of the organization. Experiential programs like design thinking exercises and group problem-solving have proven to be more effective than other approaches. Position-appropriate exercises for staff at every level can show the benefits of analytics and data-based decisions. Not only education should focus on attitudes and knowledge about data, analytics, and AI, but also on the ability to find and manipulate data at every level, including senior management level.
According to a survey by the data analytics vendor ‘Splunk’ of 1,300 senior executives. While 81% of the executives say that data skills are a must to be a senior leader in their companies, 67% mention they will not prefer accessing or using data themselves. 73% feel that data skills are difficult to learn than other business skills, and 53% were certain that they are too old to learn data skills. Yet, effective education initiatives can prove them wrong.
Leading by Example
Leading by example is essential. This requires presenting leaders who use analytics and AI in their internal marketing programs to disseminate the value of the approach within an organization. Leaders’ exemplary behavior includes demonstrating the coveted attitude about data and analytics in meetings.
While only a few leaders can see the importance of marketing their use of data and analytics, companies are designating champions of AI. According to the 2018 Deloitte “State of Enterprise AI” survey, 45% of U.S. executive respondents said their company was employing senior management champions. So, establishing communities of practice around analytics and AI is yet another method to showcase positive instances.
Rewards
Promotions and rewards can also bring change. If those who make effective use of data and analytics get promoted faster or their salary increases. It will encourage others as well. This approach needs leadership endorsement and execution by Human Resources.
Conclusion:
Today, every job needs an orientation toward technology, and with elementary tech-savvy, employees don’t only need to have the basic skill requirements in a changing competitive environment, but also the attitude to sustain a flourishing data and Predictive analytics culture for decision making. Cultural evolution takes a long time to develop, and culture the leader who becomes a part of an organization. So, someone needs to check changes in the data/analytics orientation of the leadership team.
When it comes to establishing a data-driven culture, there’s no rest for a weary person. Many organizations focus on data and analytics, yet, when the CEO champion vamoosed, they went back to their old gut-based thinking and decision-making. Thus, CEOs and AI leaders who believe in this focus must work to encourage others to adopt it.
