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Data Analysis to Rule a New Manufacturing Era – Part 1

As the world slowly recovers from the Great Recession, the competitive landscape for at least one sector – manufacturing – is entering a new era, ripe with opportunities but also fraught with challenges, according to a new report from McKinsey Global Institute.

developpement capteurs optiques sensor development Data Analysis to Rule a New Manufacturing Era – Part 1The winners in the global manufacturing arena will be those companies that can adeptly harness big data with manufacturing analytics to uncover customer insight, identify new markets, monitor sensors and collect after sales data.

This is the first article in a series that delves 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.

While economists are debating whether the US economy is undergoing a manufacturing revival, there can be no doubt that globally, manufacturing continues to grow. In fact, it now accounts for about 16% of global GDP and 14% of employment, according to the McKinsey report.

Over the next 15 years, another 1.8 billion people will enter the global consuming class and worldwide consumption will nearly double to $64 trillion, McKinsey predicts.

“The new era of manufacturing will be marked by highly agile, networked enterprises that use information and analytics as skillfully as they employ talent and machinery to deliver products and services to diverse global markets,” the report notes.

One of the biggest opportunities for manufacturers to tap into the power of data analysis revolves around unearthing actionable customer insights. By 2025, the majority of global consumption will take place in developing countries, while customer demand in established markets is expected to fragment as consumers ask for greater product varieties.

This creates a need for manufacturers to combine structured data from transactions with unstructured data from various web outlets including social media and mobile devices to be able to meet customer demands.

“In customer facing activities, social technologies can generate deeper customer insights to fine tune product development and provide a way for customers and other outside contributors to participate in co-creation of new products and features,” according to the report.

The report goes on to note that across four manufacturing sectors – CPG, semiconductors, automotive and aerospace – social technologies could provide potential margin improvements of 2 percentage points to 6.5 percentage points, “providing companies can transform traditional manufacturing IT into an all-encompassing information strategy to fine-tune product requirements, improve manufacturing processes and boost quality and productivity.”

Exploiting big data through data analysis can make “substantial improvements” to how companies respond to customer needs if they can effectively gain insight from large databases and online chatter about brands or products, according to the report.

“Companies must develop a detailed, granular view of markets and customer segments to identify and tailor products and supply chain strategies to specific sub segments of markets,” according to McKinsey.

Segmenting the Chinese market, for example, on a national or regional/city basis is not adequate, the report notes. However, by analyzing consumer characteristics, demographics, government policies and other factors, the study identifies 22 distinct market clusters that can be targeted independently.

But while many B2C companies have become adept at using analytics to mine big data for new granular micromarkets, the concept is relatively new to B2B companies, notes a Harvard Business Review blog post. Moreover, this could provide one of the most effective uses of data analysis for B2B organizations.

Here’s how to uncover granular micromarkets with data analysis:

Use insight about growth opportunities to rethink how sales representatives are assigned. Consider the case of a chemicals company,” HBR notes. “Instead of looking at current sales by region, as it had always done, the company examined market share within customer industry sectors in specific US counties. The micromarket analysis revealed that although the company had 20% of the overall market, it had up to 60% in some markets but as little as 10% in others, including some of the fastest-growing segments. On the basis of this analysis, the company redeployed its sales force to exploit the growth.”

Identify groups of micromarkets that share common characteristics. Once groups are grouped together, marketing managers can develop common strategies for how to best sell into that particular market.

“For example, the chemicals company grouped its 70 micromarkets into four peer groups and outlined a strategy for each, such as ‘invest,’ in which it sought to capture an outsized share of growth, or ‘maintain,’ in which it sought to hold on to its market share while maximizing operating efficiencies,” according to HBR.

Provide experiential training for sales team. Reps should be provided with hands-on opportunities to see data analysis in action. Some companies have created in-house laboratories where sales and marketing coaches help sales reps tailor their pitches for new micromarkets.

“Finding growth with big data is more than an add-on; it affects every aspect of a business, requiring a change in mind-set from leadership down to the front lines,” the HBR post notes. “Micromarket strategies are demanding, but they consistently give sales a competitive edge. Sales leaders should ask whether they can afford not to embrace big data.”

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Heather Harreld
Spotfire Blogging Team

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