Based on our research on digital transformation, Trianz has found that more than 70 percent of companies do not have the analytical skills to account for seismic changes in their market, which means that companies only draw strategic conclusions from available or appropriate data.
This is an approach that always falls short.
If the digital change takes place on a massive scale, the perspectives on the “available data” will be outdated and never holistic. By the time the data was collected, the landscape had changed, making the strategies developed from the data obsolete. Your strategies and executions the first time.
That’s a big part of the reason I wrote my book; to help leaders use the skills necessary to learn from the past, analyze the present, and predict the future. These are your keys to crossing the dividing line.
So how do you use the skills needed to replace assumptions with data analysis? First, let’s examine the data ecosystems available to any business.
Data: The Open Secret in Your Ecosystem
For a strategy to be truly effective in the digital age, it must be highly adaptable to change. To be inherently adaptive, it must constantly rely on collective and predictive information.
To do this, you need to extend your analytics capabilities beyond the traditional ecosystem of customers, suppliers, and employees and analyze competitors, partners, regulators, and influencers. While these latter interactions may be non-transactional, they provide ongoing data in the form of conversations about new models, research, technologies, innovations, or opinions that are influencing others.
Only by analyzing all of this data on a regular basis can you develop a holistic view of your stakeholders and develop a competitive or breakthrough dynamic that creates a data-driven culture.
Only then will fact-based decisions drive innovation.
The Four Stages of Digital Maturity
While it makes sense to eliminate assumptions and prejudices, it is not that easy to get there. Habits, organizational dynamics, and long-established turf wars can override the practical logic that arises from data-driven insights.
To eliminate internal challenges, it is vital that your company’s data and analytics are mature. These degrees of maturity can be summarized in four levels:
Level 1 – Reports: The first level is the ability to generate reports for your company; You should know what happened yesterday.
Level 2 – Business Intelligence: The second maturity level is business intelligence and dashboards or the ability to know what is happening today.
Level 3 – Predictive Analytics: By investing in data science algorithms, you can develop the ability to predict what is likely to happen in your company will happen.
Level 4: Prescriptive Analytics and Artificial Intelligence – Once you gain control of your data and understand the human behavior that affects your analytics results, your business can generate prescriptive information that, in many cases, can be further automated with Artificial Intelligence in your business do faster, high quality results with less human intervention.
Since most organizations today only have basic reporting capabilities, legacy players should take advantage of predictive analytics as soon as possible. When you are able to understand, analyze, and interpret the data generated in your company and your environment, you can replace assumptions with facts and catch up or be ahead of the competition.
The cumulative effect of replacing assumptions with data-driven analytics is to break down organizational silos and quickly learn that the stakeholder expectations revealed by data are more important than opinions and biases.
