Business challenges are different now to what they were back in an earlier generation. So, the leaders too need to evolve likewise, especially when it comes to their proficiency with technology. The CIO needs three vectors for a holistic transformation. The first of them is about reimagining the role of technology to any organization. The technology delivery too needs a reinvent. One has to future- proof the foundation as well. There exist some basic traits that any transformative CIO of today needs to possess. As a business leader, he/ she needs to gather authentic business intelligence, to gauge the trends in and out. Responsibility ought to be taken which will lead to the adoption of initiatives that will generate revenue. The person must also be a part of different corporate boards. The CIO also needs to be a change agent. His/ her talent recruitment capabilities need to be strong. This will help build internal talent as well as manage to attract the tech stars. A cultural revolution needs to be brought out. He/ she will also need to be a tech translator. This will help align the business decisions with the existing tech capabilities.

Source:https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/the-cio-challenge-modern-business-needs-a-new-kind-of-tech-leader

Uploaded Date:27 February 2020

Disruption is now a constant enabling sector- specific boundaries to now become permeable. Algorithms, artificial intelligence and data warehousing capabilities have changed how companies approach forecasting and decision-making. Due to this companies are focusing on digital transformation. A lot of management training programmes have been held with the motive to bring agility into the workspace. But all this is bound to fail unless one develops inner agility, as opposed to the natural stasis sought. As building blocks towards this one must take the occasional pause to reflect. Ignorance in any field must be embraced and rectified. Questions need to be framed to pose at all times. While the final objective is crucial, the journey one undertakes is equally so. Any solutions crept up, must be tested around others, as well as oneself.

Source:https://www.mckinsey.com/business-functions/organization/our-insights/leading-with-inner-agility

Uploaded Date:21 February 2020

In order to reshape how product development will take place in the future, generative design could be a highly useful tool. Once the original part is received, is when the generated design can work on it. This will lead to the final engineered output. For these algorithms to succeed, high- level data warehousing is to be done. The process must begin with the initial concept. This will be followed by the detailed design and engineering. Over time, product improvement will take place. Procurement would be final stage. There are challenges and opportunities, but also enablers to take the process forward smoothly. Design tools are also evolving.

Source:https://www.mckinsey.com/business-functions/operations/our-insights/how-generative-design-could-reshape-the-future-of-product-development?cid=other-eml-alt-mip-mck&hlkid=2a8ab0dc6a8c4c1a886bd1fde97b8b8d&hctky=9953462&hdpid=0a34d40d-1e3d-416c-9c80-3aa89ac3d33b

Uploaded Date:21 February 2020

The general feeling among some of the newer users of business analytics and algorithms, is that these are there to replace human managers. But in reality, those who have experienced the grind, are aware that a seamless combo is far more effective. Algorithms too require managers, in order to extract the required business insights. Smart algorithms on their own have the propensity to lead their users astray. One of the obvious reasons for that is that they are far too literal in their approach. They are also like black boxes, in the sense that they do find out the factors, but fail to indentify the real reasons behind someone’s success or failure. Managers need to be explicit about the end goals they are seeking. The myopic view has to be replaced with a far- sighted one. Usually, the data captured leads its users towards short- term outcomes, as a result of the algorithms’ focus on data at hand. For the requisite data warehousing, the team needs to be aware of the right input sources. Diversity is key. Before work begins, the manager must also be aware of the limitations that such data imposes upon the user.

Source:https://hbr.org/2016/01/algorithms-need-managers-too?utm_campaign=hbr&utm_source=facebook&utm_medium=social

Uploaded Date:28 January 2020