How to be a digital leader in a time of large-scale technology transformation
Following interviews with hundreds of industry executives, McKinsey recently shared fivecornerstones that are enabling organizations across every industry to integrate and capitalize on advanced technologies such as analytics, AI (artificial intelligence), machine learning, and the Internet of Things.
These cornerstones of large-scale technology transformation include:
- Developing technology road maps that strategically focus investments needed to reinvent legacy businesses and create new digital ones
- Training managers to recognize new opportunities and build in-house capabilities to deliver technologies
- Establishing a modern technology environment to support rapid development of new solutions
- Focusing relentlessly on capturing the strategic value from technology by driving rapid changes in the operating model
- Overhauling data strategy and governance to ensure data is reliable, accessible, and continuously enriched to make it more valuable
When it comes to the latter, McKinsey says that while every executive understands data will yield a competitive advantage (MicroStrategy’s Global State of Enterprise Analytics Report 2020 shows that 94% believe data and analytics are important to digital transformation and business growth), few have put in place the business practices to capitalize on it. For most, the data is messy and hard to access, and current technologies cannot scale to take advantage of a fast-growing wealth of data sources.
Constellation Research founder and Disrupting Digital Business author Ray Wang says this is what's driving the growing divide between digital leaders and laggards, one where digital leaders are taking 40-70% of market share in the future of data in digital transformation.
'Digital leaders are folks that understand the impact of data', says Wang. 'They understand how to ask the right business questions. They understand that integration is important. They understand why data quality is needed. They understand why testing is so important before releasing something, because if you don't properly test, what you end up with is a lot of bad insights and next best actions which reduces the confidence in the data. They understand the human factors behind data and data design'.
'They're always looking for new data sources and how to get those data sources to work', continues Wang. 'And they're always trying to figure out how to empower people with not just data, but the ability to make better decisions'.
'Using data effectively in digital transformation is not easy. To make it work, you've got to have your data house in order. Build a foundation to support strong governance, data prep, streaming, and agility'.
Author: Tricia Morris