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As Tiger explains, start by asking yourself what kind of outcome your business is trying to deliver. That could mean helping a client achieve a specific goal or gaining market share against your competitors.
The next factors to consider are how to get started quickly, using the most current data available, while minimizing costly risks. Create a digital transformation strategy that uses predictive modeling and machine learning algorithms to help you determine exactly what data you need, gather the data in real-time, and provide a combination of data science and machine learning to create an ideal data management platform and predictive analytic tools for your business.
But this kind of digital business transformation can meet with resistance among your employees. After all, the changes you want to implement may introduce changes to your company’s working culture and processes.
For this reason, be sure to have a clear vision of an overarching, data-driven business strategy and set winnable goals for the different teams in your company. Gaining early wins around digital strategy can help employees adapt to change and be open to workforce retraining.
Information is power, and data is key. But how does a company shift forward to becoming a data-driven organization?
First, ask yourself what outcome you want. Then figure out what data you need to make that happen.
Understand that changing the way your company does business means starting at the top, with leadership building a clear vision. Then, start with winnable goals that build momentum for your team.
Also understand that retraining and re-skilling workers may be necessary to help them adjust to big changes, such as AI making the decisions they used to be tasked to make. Building excitement in your workforce can help them forge ahead instead of resisting change.
To become a data-driven organization, create a broad vision but start small and gain quick wins.
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