Manufacturers have long embraced Operational Excellence through programs like Six Sigma, quality initiatives and careful focus on scientific methods. Until recently, manufacturers have been less likely to adopt a similar approach to data choosing to make do with a silo’d approach.
This might have worked in the past, but in today's environment it will increasing undermine (if it hasn’t already) profitability and long-term success. Using the same steps that helped companies achieve operational excellence can help them reach the same stage when it comes to their information.
Big Data = Big Challenges
We recently worked with INDUSTRYWEEK and Penton Research to survey manufacturing companies on their use of data.
The survey results show that one-third to one-half of companies say they lack enterprise-wide accessibility to data, don’t effectively integrate data and do not have a consistent means to identify and analyze meaningful data.
The most interesting part of the survey: Managers and individual contributors see the possibilities of Big Data more clearly than company leaders.
Discussing data in the same framework as Operational Excellence helps mid-level managers and contributors explain the potential of Big Data in a way that their bosses can understand.
Defining Information Excellence
Information Excellence is about using data to move an organization forward. Companies that have mastered it:
Use data to understand what will happen next: Data should not be used exclusively to measure or justify past performance. Data should shed light on the multiple pathways for going forward. To understand what will happen next, organizations are constantly asking this question: Is the right data being collected? What else should we be collecting?
Eliminate data bottlenecks: Is timely data available to all whom could benefit from the insight? Can business users access data or do they need help from IT experts? Nearly half of large companies ($1 billion or more in revenues) say they’ve got data accessibility issues. Companies that master information excellence don’t rely on “IT experts” to “push” data to business users.
Employ scientific methods to analyze data: Are there standard processes for analyzing and reporting data with proven results? Is sound statistical analysis applied? Are there unnecessary filters, or are some sets of data being ignored or over-emphasized? In Operational Excellence, you must use proven, repeatable, standardized methods. Same goes for Information Excellence.
Think systematically: Taking a “big picture” view helps companies understand that the problem might not be that if they gather more data they’ll need more server space, but rather that they need a better method of analyzing what they gather. Data needs to be processed efficiently to be useful. Sixty percent of surveyed companies concur, nothing they need better analytical tools. Only 30 percent say they need more server capacity.
Create value through decentralized decision-making: Consolidating all decision-making power at the top of an organization is a model at odds with enterprises that embrace Operational Excellence. You want to push operational decisions down to those closest to the value-creating processes. Same with data. Think of it this way: If the only person getting information on a spike in warranty claims is the executive in charge of that operation, it doesn’t help the warranty people downstream who must fix the problems, the manufacturing group that needs to know that there is a problem to begin with, even the finance department that must adjust forecasts. If the warranty exec hangs on to that information for even a day or two – even inadvertently – the severity of the problem could escalate.
Building a framework to support Information Excellence
An Information Excellence strategy requires building a framework in which the entire information continuum (data, analytics, and decision management) flows through unified technology solutions; and strategy and implementation services are managed on an enterprise level.
“Unified” does not mean “one vendor” – it means the different solutions can work together and data can be integrated. And working at the enterprise level means IT doesn’t control and/or drive all decisions (though they are a key part of the discussion).
A unified approach with enterprise level management allows organizations to fully govern and exploit their information assets resulting in competitive differentiation and sustained business success.
With this approach, an organization’s data becomes a strategic asset for building business value through optimized decision-making. It’s to allow people throughout the organization to create value – just as with Operational Excellence, efficiency improvements alone won’t grow the business.
Mike Newkirk is the Director of Manufacturing and Supply Chain Solutions at SAS.
