Despite global variations in the viability of the manufacturing sector, one thing remains consistent: forward-thinking manufacturing organisations are not only finding new ways to automate and create efficiency,but they are also focusing on new opportunities for revenue growth.
And, at the centre of their quest for transforming their organisations is data, says Sanjay Ravi, worldwide MD for Discrete manufacturing: high tech & electronics, automotive, aerospace and industrial industries at Microsoft.
On his blog, Ravi writes that the most recent quarterly report from the Manufacturers Alliance for Productivity and Innovation (MAPI), a leading indicator for the manufacturing sector, showed that manufacturing in the US will grow faster than the overall US economy in 2014 and 2015.
Worldwide, projections for the health of the sector vary depending on regional economic trends and policies.
Japan’s recent increase in national sales tax, for example, is causing a contraction in manufacturing activity and JP Morgan’s global manufacturing PMI report showed a slowdown in other countries in Asia as well.
Microsoft recently sponsored an IDC study to look at companies globally to better understand what actions by “data smart” manufacturing organisations yield the most impactful outcomes – both in terms of growth and efficiency.
“The research surfaced an eye-popping number of $371-billion – the potential net value of what we refer to as the ‘data dividend’ over a four year period for the manufacturing sector if companies become data smart,” says Ravi.
He points out that data-smart organisation perform some combination of the following four actions:
* Bring together even as few as 3-4 discrete data sources;
* Use modern analytics tools to glean insights from data;
* Surface those insights in a consumable fashion to the right decision makers across the company; and
* Ensure that insights from data are shared in a timely manner.
“Manufacturing organisations that take all four of these steps potentially stand to realise a 60% greater return on their data assets,” says Ravi.
