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Deloitte's Michael Korpal. Deloitte's Michael Korpal.

How to profit from turning data into dollars

By Michal Korpal

Deloitte, Western Sydney

A RECENT benchmarking Index from Deloitte and the US Council on Competitiveness, 2013 Global Manufacturing Competitiveness Index, highlights that Australia ranked at number 16 in terms of current competitiveness compared to number 15 in 2010.

Furthermore, according to the survey, the competitiveness of Australia’s manufacturing sector will continue to decline - in five years it is expected to rank 17th against other national economies.

The Global Financial Crisis has exacerbated the impact of long-term challenges facing manufacturing in Australia. Since the beginning of the crisis in 2007 nearly one out of 10 jobs in manufacturing was lost and the sector’s share in the national economy measured by the level of output has shrunk from 10% to 8%.

Western Sydney is one of Australia’s largest manufacturing regions and it is hardly a surprise that the toll taken here by the Global Financial Crisis is higher than in most other parts of the country.

The manufacturing industry contributes 13.5% of Western Sydney’s Gross Regional Product and is largely represented by small and medium Enterprises (SMEs).

This produces another challenge for the region – an industry structure featuring disproportionately small firms may translate into fewer economies of scale, difficulties in connecting to global supply chains and the resulting lack of innovation.

In particular, the weak penetration of global value chains is a worry. In today’s global economy, participation in these value chains has become an important source of technology and knowledge dissemination.

When it comes to manufacturing, innovation is often confused with invention of new products or technologies. In reality it is equally important to generate fresh ideas of how to add value to existing practices.

Make them more efficient and cost-effective. Such innovation is often achieved “step by step” by implementing small changes to business behaviours and practices. It is a critical driver of competitiveness in the longer-term. An effective use of large amounts data could be an important source of incremental innovation.

Today, all organisations – regardless of their size – are inundated with data pouring in from many directions: operational and transactional systems; scanning and facilities management systems; inbound and outbound customer contact points to name a few. It’s structured and unstructured, messy and overwhelming, in incompatible formats, and often redundant and out-dated.

Yet this flood of data can have huge strategic value for organisations that know how to quickly turn it into valuable and timely insights. That’s where analytics comes in. The right analytics tools give managers quick visibility into business performance, customers and even the future.

At the same time, fast access to insights can make employees more productive and empower them to make faster, better decisions that lead to improved business performance. The use of data analytics to enhance “repair and maintenance” processes demonstrates how incremental innovation can be achieved in a medium-sized manufacturing business.

A machine component failure analysis can be performed based on historical data to pinpoint and address failure trends. The analysis is likely to produce valuable insights due to its granular nature and consideration of multiple predicting variables.

This in turn will result in less breakdowns and repairs. It will also contribute to reduced risk of process disruption and lower wastage and factory maintenance costs. Moreover, once the relevant data has been identified together with its sources and a proper framework has been established to analyse it, management can monitor effectiveness of repair and maintenance practices on an on-going basis and identify further business process improvements.

Another example of how data analytic techniques can support decision making in a manufacturing environment is represented by an exercise to optimise inventory levels and reduce complexity across an array of products.

A business-to-business manufacturer with thousands of products on hand recently performed granular data analysis to understand margin contribution on an individual product level. The aim was to identify low margin products that might be discontinued.

Due to the complexity and volume of data, the use of data analytics significantly reduced the time required to complete the exercise. Further meaningful insights could be achieved by overlaying these findings with customer data in order to rank product/customer data relationships based on their profitability.

Equipped with these insights management could make more informed decision to invest in high-performing products and nurture profitable customer relationships.

This in turn will contribute to increased return on investment. Nowadays manufacturers are compelled to innovate more rapidly than ever in order to protect their competitive edge and survive in the market.

According to the 2013 Global Manufacturing Competitiveness Index, talent-driven innovation is the most critical driver of the sector’s competitiveness. It ranks even higher than governments’ economic and fiscal policies, or the cost and availability of labour and raw materials.

The pressure is on. How does your business embrace economic challenges faced by our region? Smart use of data will help you innovate to make your business more competitive.

Contact Michal Korpal at Deloitte, Western Sydney. Phone 9840 7354 or email mikorpal@deloitte.com.au



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