Analytics without question can help industrial manufacturers gain a competitive edge. But, given the prolonged economic slowdown, some companies may not be using analytics enough to help sustain high performance through this tough time. Operations, the heart of industrial goods and services production, is particularly vulnerable during recessionary periods because of volatility in demand. If ever there was a time when companies need to increase development of their analytical capability to understand how best to predict and manage the operational inefficiencies and high costs associated with fluctuating demand, it is now.
But, a recent Accenture survey of 600 executives at more than 500 top organizations in the United States and United Kingdom that included interviews across industries and functions, suggests analytical capability in the area of operations is underutilized. For instance, just over one-third (35%) of U.S. respondents said they apply analytics in their operations area, and only 34% plan analytics investments in this area in 2010. Some may be relying on less formal decision-making processes or have an organizational structure that inhibits greater use of analytics. But, whatever the case, companies will need to more aggressively pursue analytics to produce a lasting competitive advantage.
High-performance businesses -- those that substantially outperform competitors over the long-term and across economic cycles -- are five times more likely to use analytics strategically compared to their peers, according to our research.
There are three actions industrial manufacturers can take to strengthen their analytical capability, produce better business outcomes, and continue on the path to high performance.
- Recognizing the old and new obstacles to achieving better analytics
- Diagnosing the state of analytics within operations
- Ensuring thoroughly analytical operations
Building an advanced analytical capability is not easy. Even well-intentioned manufacturers may struggle to generate insights from their technology investments, connect their insights to the relevant processes, and then link them to tangible business outcomes. And, while each company has its own unique set of challenges, most tend to share one or more of several common obstacles that can impede producing superior analytics.
These can include focusing on the wrong metrics or too many of them. Most companies establish a large set of metrics, but they often lack a causal mapping of the key drivers of their business, which a small set of metrics should track. Then too, there can be an over-reliance on technology as a solution. Too often, companies build a large data warehouse or an enterprise resource planning system and assume that decision-making will improve. But, a key factor in meeting that objective, is putting technical tools in the hands of the right, analytically oriented people, architected around the right process, in order to drive an outcome.
Another challenge involves having too much data. Like many companies, industrial manufacturers can be burdened by a proliferation of data volume that can impact effective use of analytics. Without a proven process for selecting the right data to analyze, it is unlikely that a company will be able to discern important patterns that can lead to smarter decisions. One-off solutions, too, can hinder more than help. For example, until a marketing analytical capability is connected to all pertinent facets of operations, such as how the product gets to customers and how the manufacturer can enhance customer service through it, this capability will be sub-optimal at best.
Change is always a challenge. Companies that have become accustomed to primarily basing decisions on intuition and experience rather than fact-based analysis, can no longer afford to do so. The growing complexity of the global marketplace requires much greater insight into customer preferences and competitive challenges that only robust analytics can support.
Next, the route to building an analytical capability will depend on the level of analytical maturity currently within the company and its operations. Therefore, an initial diagnostic to determine current maturity and where the gaps lie should be performed. Manufacturers that are beginning to develop analytics should aim to improve the quality of data or technical tools. Poor data quality is prevalent around the globe. If dirty data is an issue at an organization, it is essential to determine what is the highest priority data for executing the core strategy, and then validate, clean and consolidate that data.
Also, companies at this stage are often short of people with strong analytical skills -- the specialists with the know-how to make a real difference. It is critical to make such talent part of the analytics development process. Manufacturers that are further along have already improved the quality of data and brought analytics specialists on board.
Finally, to produce effective analytical capability industrial manufacturer operations will need to become thoroughly analytical. They will be able to do so by building their capability on a three-part foundation. This includes, first, developing disciplined, repeatable processes to ensure that valuable insights and recommendations are generated, acted on, and their effectiveness measured. Second, it is essential to select the right people with the right skills to identify the insights, and then put them to work. And, third, companies must use technology that ensures data integrity, quality, and accessibility.
Strong Analytical Capability is a Must Today
The enduring troubled economy, increasingly, is making the need for effective analytics more crucial to the success of today's companies. Industrial manufacturers that can harness its full power, not only will have an opportunity to experience better business outcomes and high performance in the current economic environment, but will be able to position themselves to sustain high performance in the next economic cycle.
James Robbins is a senior executive for Accenture, a global management consulting, technology services and outsourcing company.
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