4 Jul
2018

The 3 Central Tasks of Data-Driven Transformation

BCG's cost-effective and evidently successful three-step approach addresses a timeline for digital transformation in companies across sectors. The approach begins with pilot projects of rapid digitization to a final data governance system leading to a full-fledged digital transformation.

Analytics
Industry 4.0
The 3 Central Tasks of Data-Driven Transformation

 

 

Data-driven transformation has taken to drive change in public and social sectors. Such change has motivated most executives to find reliable ways to propel their companies into data-based futures. Along with motivation, fear to keep up with competitors and ensure survival of their businesses pushes CEOs to implement a focused, pragmatic, and agile approach to data transformation. Working with different industries, BCG has addressed this challenge and developed a cost-effective, sustainable, and progressive three-phase approach:

 

Worximity - Data driven transforamtion with Smart Factory technologies

1. Funding the journey 

Entails laying the foundation with rapid digitization efforts that address the basics of broader transformation and deliver returns that can fund later phases. The benefits of these pilot projects help to show how an example company can benefit from digitization in the long run.

2. Designing a company-wide transformation 

Focuses on optimizing performance through digitization. In this phase, companies should draw on wins from phase one and create a detailed roadmap for extending transformation to other areas of the enterprise. Additionally, identifying benchmarks to digitize functions and operations allows companies to prepare for a full-fledged digital transformation. In this phase, it is also helpful for the organization to start “industrializing” data analytics—using analytics as a resource for each operation.

3. Organizing for sustained performance 

Involves building long-term systems and working towards using new data-driven strategies. As the company continues to sketch its transformation roadmap, it should standardize data-based systems for an effective output. Finally, to ensure sustainability of adopting digital processes, companies should constantly encourage new ways to use data.

 

Data-Driven Transformation_ex02_tcm-156856

 

SOURCE:  https://www.bcg.com/fr-ca/publications/2017/digital-transformation-transformation-data-driven-transformation.aspx?linkId=52354074&redir=true

Want to learn more?
Download the ebook
Related blog articles

Related articles

Back to the blog
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
21
Jul 2023

CDAP: $15,000 Grant To Jump Start Canadian Manufacturing Digital Transformation Projects

English
13
Jul 2023

5 Ways Production Monitoring Helps Reduce Turnover and Bridge the Skills Gap

English
28
Jun 2023

Investing in Industry 4.0: It’s now more important than ever for food & beverage manufacturers of all sizes

English

Related articles

Back to the blog
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
30
May 2018

How to Get Started as a Developer in AI

For developers, the expansion of the AI field means that you have the potential to apply your interest and knowledge of AI toward an industry like the manufacturing industry.

English
6
Dec 2018

AI in Baking for Real-Time Predictions

Get to know more about Dutch powerhouse Bakkersland and their experience with the implementation of AI in their factories.

English
15
Feb 2018

Harvard Business Review Article on Artificial Intelligence

AI won’t replace managers, but managers who use AI will replace those who don’t. Learn what artificial intelligence can do for your business.

English