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Digital Transformation

In the ongoing Industry 4.0, digital tools are also needed for maintenance of equipment. But the existing ecosystem often does not allow for this. The CMMS (Computerized Maintenance Management System) and ERP (Enterprise Resource Planning) infra do not always align well with digital operational tools. The user interface may often be complex so better work-management alignment is needed. To understand this better business consulting giant McKinsey has come up with a poll among the practitioners. This will enable the company to gauge reliable insights which can then be used to devise solutions. The poll is an online two-minute survey.

Source:https://www.mckinsey.com/business-functions/operations/our-insights/operations-blog/how-well-are-digital-tools-serving-your-maintenance-organization

Uploaded Date:15 November 2018

Manufacturing concerns are on the cusp of a golden opportunity to reap the outsized benefits of digitization’s early promise. This has been made possible due to the widespread use of artificial intelligence, robotics, cloud computing, smart sensors and the pools of big data. An impact of this digitization is that outsourcing to low-wage countries in Asia, Latin America and Eastern Europe maybe on the wane. One of the features of the ongoing Industry 4.0 is thecustomization that can be effected for segments of customers. For this, the technology spine needs to be modernized. Drones are an example of how quickly business processes can be executed. Before moving forward, one has to understand the difficulties that will arise on the way. A six-step plan has been devised to take this ahead. There must for a start be a digital factory strategy fully mapped out. This needs to be followed by pilot projects being executed. The capabilities needed have to be clearly spelt out. Lone needs to make full use of business analytics to mark the transition. Instead of physical factories, there must be a move towards digital ones. These digital factories eventually need to get aligned with the overall digital ecosystem.

Source:https://www.strategy-business.com/special/Inside-the-Digital-Factory?gko=b4d31

Uploaded Date:14 November 2018

During the tough phase of digital transformation, some key enterprise architecture practices need to be kept in mind, as they have been known to add value. To start with, the top executives need be involved in the decision-making process. There must be an emphasis in planning for the corporate strategy. More than the process of transformation alone, due emphasis must be paid on the outcomes to be achieved. Alignment has to be achieved between the IT and its business capabilities. This is because the technology is no longer limited to be an aid, but a key ingredient in the stack. Capability maps may be built to assess any gaps. During the transformation phase, it is essential that the company wins the in the talent recruitment stakes. But beyond that, the talent has to be honed and retained. The training process needs to focus on the enterprise architects.

Source:https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/five-enterprise-architecture-practices-that-add-value-to-digital-transformations

Uploaded Date:13 November 2018

In order to build a sustainable digital business, a digital data architecture is needed first. This data-driven approach is the key difference between the leaders and laggards. A lot of companies instead use a tech-first approach. This approach leads to an inconsistent and redundant data warehousing. As a result, it gets cumbersome to extract insights when needed.This model is not sustainable over a period of time. It leads to an overlap between the functions to be performed. The present model requires added speed due to the diverse sources of information seeping in. Thus, the two-speed principle needs to be applied which adds new age speed to legacy IT systems. This system helps the transparent management of data flows, to protect against data inconsistencies or the formation of silos. One clear demarcation of capabilities has been effected, operational reporting and advanced business analytics get easier to implement. In addition to the warehousing already mentioned about, the architecture needs to address the data consumption and distribution. A master data management infrastructure has to be built in. The sourcing points too need to be specified.

Source:https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/why-you-need-a-digital-data-architecture

Uploaded Date:13 November 2018

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