Each time an organization is looking on how to improve their overall business efficiency or finding new ways on how to generate new revenue opportunities, creating business models, or launching new markets, it all comes down to one key thing: available data. 

Nowadays, the Data and Analytics space augmented by AI solutions equips organizations with distinctive capabilities, creating top-notch players on the industry that are clearly differentiating themselves from competitors for their ability of rapidly enabling decision makers by providing timely and accurate insights, accelerating growth opportunities. 

According to recent studies more than half of the organizations with high operational maturity are already scaling data and analytics capabilities. This is visible if the organization is: 
 
– Continuously exploring how to expand their available data sources and on top of that, they are enhancing the use of it through AI related initiatives. 
 
– Leveraging high quality data for decision making and augmenting people’s capabilities with technology and agile working models, 

 – Ultimately, being in position to scale siloed AI pilots across the organization and move towards a data-driven-enterprise-wide analytics transformation. 

How can AI Enablement support stakeholders on data driven decision making? 

 When AI is adopted at an organizational scale, stakeholders at all layers will augment and accelerate their own judgment and intuition supported by algorithms’ recommendations to arrive at better answers than either humans or machines could reach on their own.  
 But for this to work seamlessly, there needs to be a sort of partnership or bond established between people themselves and the AI-algorithms’ recommendations, so that the employee would feel empowered to make decisions. In most cases, this also means reshaping our organizational culture, moving away from the traditional hierarchical top-down approach and siloed knowledge. If employees must consult and escalate issues higher-up before making decisions and acting, the use and real power of automations and AI will be simply diminished. 
 The essence of an organization is heavily influenced by how it operates – and any changes on the operational landscape will have an effect across the whole organization. 
 Organizations with a higher level of operational maturity tend to be more efficient and profitable, as they also improve their human workforce talent and skills, fostering employee retention and engagement. 

First steps towards growth acceleration 

How can we work towards improving our organization’s operational maturity so that we can move closer to an AI-Powered strategy that enables data-driven decision making? 

Understand the WHY: Have an aspirational vision in mind and start your journey. Understand and constantly reassess the trade-offs and changes to be done to bridge the gap between the current status and the desired one. Be ready for challenging your status quo continuously, aiming to scale best practices across the organization. 

Scale automations: Strive to deploy end-to-end automated processes, using AI wherever it adds value. 

 Foster ‘Human+Tech’ partnership: Seek for efficiency improvements through use of technology to support employee’s daily work, leaving them more time to perform tasks which require critical thinking and creativity. Employ technology to cover repetitive and tedious tasks, meanwhile adopting business agility practices at scale to release value seamlessly and ramping up capacity as needed. 

Improve data quality and start following a data-driven decision approach: We all agree that the human intuition and experience have always been key factors influencing decisions. But as our organizational horizons expand, there is a need of having a more comprehensive and global approach, supported by high quality data which would ultimately support the decision-making process. 

Try to assess and leverage all potential data sources available and take data quality to the next level, making it available to key stakeholders so that the decision-making loops can be closed timely and efficiently. 

Even though this is not a plug-and-play type of a journey, having in mind the following points will support us on each step of the journey: 

-In many occasions will require from all employees to adjust ways of working, roles, and culture,  
– The data that we have today and how we use it will support on answering questions from tomorrow. 
– The organizations which would successfully leverage the use of AI throughout the organization will take it to the next level making the best out of the human and technology partnership.