What are the leadership skills needed to drive effective change in organizations to achieve data and analytics excellence?
The key challenge organizations face in achieving data and analytics excellence is in driving consumption of analytics. In my experience, I have observed that most organizations decisions are based on the 'sense' decisions makers get as opposed to data-based analytical insights. To overcome this, the key skill required is developing a data-driven mindset within the organization. Proactively educating the organisation and demystifying analytics for the company is key to promoting acceptance and execution.
Additionally, industries are rapidly evolving and the need of businesses is fast-changing. Therefore, it is vital that organizations have SMEs with awareness of the industry and a continuous learning mindset. Being agile in analytics implementation and adopting best-practices is essential. Analytics being a new space, companies still need to ramp up. This takes time and organizations need to have patient yet decisive leadership team members. Lastly, to achieve true excellence w.r.t. data and analytics, organizations need to be thinking into the future and build a well-planned analytics roadmap which involves building the IT infrastructure, BI analytics and set SMART data-driven business goals for stakeholders to achieve over the course of a year.
Can artificial emotional intelligence be a substitute for real emotional intelligence?
Not yet. We aren't ready to lose the EQ aspect especially in the healthcare, entertainment and hospitality industry. It has been ingrained in us, to expect a certain kind of service and benefits out of the same. We wouldn't prefer for example, a nurse who would sequentially treat us based on our illness or certain emotions. We still prefer the assurance and re-assurance at every step of a treatment. Eventually, yes. As more of us get immersed in our daily lives, spending the constantly increasing time over social media or other aspects, we are anyway losing human connect.
Artificial emotional intelligence can play the human-like role through this new media of interaction. There needs to be a balance. Some services can definitely be replaced to bring down costs and time while others may take much longer to evolve and accept.
What does sales analytics mean?
Analytics that can help improve the entire lifecycle of a sales effort. This can include aspects like tracking the progress of your sales-force, improving the incentivization schemes, understanding at which AIDA stage a customer drops off, or improving the way of doing sales. Data-driven decisions through BI, models or data exploration can help answer these aspects.
What role does analytics play in measuring the engagement level of employees?
People are the greatest asset in most companies. Services especially, primarily runs on people skills. The industry may be moving towards auto ML and more AI, but people are required to still train these models or do the work. Hence, it is essential to understand their engagement level and ESAT scores. Analytics helps to understand sentiment of employees who leave, helps derive patterns of common quitting time periods, understand employee expectations w.r.t. benefit or quality of work or appraisal. While past data helps measure and predict , to avoid foreseeable circumstances, video and image analytics could help understand employee emotions and expectations more real time.
How can data scientists and analysts improve their communication skills?
Yes, some of us are so technical that we miss out on polishing our soft skills. A lot of reading and learning is also more around technical content. We definitely need to train analysts in business communication and story-boarding. Communication is extremely essential in this industry where volumes of data, math and jargon needs to be synthesised. The story and it’s communication is of essence as all the understanding needs to be stitched together to enable business stakeholders to make a tangible and informed decision.
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