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Digital Transformation

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

Amidst the growing chorus for digital transformation to be worked out better, some inputs have already arrived from companies that have already executed this tough task correctly. First of all, the clear priorities need to be neatly laid out. The next step is to invest heavily on the talent. This must be especially true for the top level. Management training programmes need to be invested on. Some of the most cutting- edge requirements need be focused on, such as for business analytics. All this will require time and money, so this must not be compromised upon. The team processes must be run on agile mode, rather than the traditional hierarchical structures. The people in the team must also get empowered so they may take the right decisions at their level.

Source:https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/digital-transformation-improving-the-odds-of-success

Uploaded Date:06 January 2020

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