Developing countries have been the go-to options for US manufacturers for many years because of low labor costs. But a new global consuming class will have emerged by 2025 and the majority of consumption will take place in developing economies, according to a new report from McKinsey Global Institute.
This will provide a wealth of new opportunities for manufacturers in these emerging markets, especially given the recent decline in US manufacturing during the recession, according to the report.
But these opportunities are developing in a volatile new landscape with dramatic swings in the cost and availability of things like labor and natural resources – a landscape that combines with rising complexity, uncertainty and risk to create an environment that is far more uncertain than it was before the Great Recession, according to McKinsey.
“The way footprint decisions have been made in the past, especially the herd-like reflex to chase low-cost labor, needs to be replaced with more nuanced, multifactor analyses,” the report notes. “Companies found that creating the right strategy for the specific segment requires granularity of focus. Companies can’t do this from a distance – it needs to be done locally, and it requires analytical rigor.”
In this second article in a series, we delve into how manufacturers can effectively compete domestically and globally in the new post-recession era by wielding big data as a weapon to drive innovation and growth.
Manufacturers must use data analysis to weigh factors such as access to low-cost transportation or to skilled employees and predict actions to offset uncertainties like the fluctuating price of materials, the report notes.
“The result could very well be a new kind of global manufacturing company – a networked enterprise that uses big data and analytics to respond quickly and decisively to changing conditions and can also pursue long-term opportunities,” according to the report.
IT research firm IDC notes that manufacturers have a significant interest in using manufacturing analytics to exploit big data. In fact, 52.7% of all manufacturers consider big data tools to be important or very important to their supply chains, according to IDC.
In addition, IDC predicts that manufacturers can tap data analysis for warranty analytics, enterprise asset management and monitoring equipment performance.
“Ultimately, the value would come from knowing in advance if the current supply chain performance would impact customer orders, notes Kimberley Knickle, practice director of IT priorities and strategies for IDC Manufacturing Insights.
Still, manufacturers will face challenges including managing data quality and data governance and finding people with the right skills, Knickle adds.
Companies starting on big data journeys should take a series of steps to tie strategy to performance, note Dominic Barton, the global managing director of McKinsey, and David Court, who leads the firm’s advanced analytics practice, in a Harvard Business Review blog post.
The pair advises companies to take these steps to effectively use data analysis to bolster performance:
- Detail the business impact they expect at every stage of a large data analysis project to better align efforts and determine priorities.
- Identify big data resources and gaps. “We often find that consideration of required internal and external data will often spark ‘aha’ moments – as executives identify ‘data gems’ cloistered inside their business units or recognize the value of creating the right kind of partnership,” according to Barton and Court.
- View data analysis in the context of competing strategic priorities. “Data strategies are likely to be deeply intertwined with overall strategy and therefore require thoughtful planning when a company decides how its resources should be concentrated to achieve the desired results,” note Barton and Court.
- Understand the big organizational implications. The threats and opportunities that are associated with big data often require changes within the organizational structure of a company that only senior-level executives can manage.
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