A new study by Ventana Research Inc. says most manufacturers fail to exploit the significant operational, marketing...
and financial decision-making benefits of manufacturing analytics. Nearly two-thirds use time-consuming, unreliable spreadsheets for their business analytics, and many say the information is stale or unreliable.
The missed opportunities may be especially acute in supply chain analytics, which can provide helpful insight into market demand and send alerts when sales deviate from forecasts, according to Robert Kugel, the report’s author and senior vice president at the Pleasanton, Calif.-based research company.
“Having good information systems enables you to compress the time to discover what’s going on, decide what to do about it and then implement an action plan,” Kugel said. For manufacturers, that often means using analytics during high-volume seasons, such as back to school. If sales are falling short of the forecast, timely analytics can help companies decide if the most cost-effective remedy is to shift production or start a co-op advertising program that moves a specific product line with deep discounts, rather than just slashing prices across the board.
But cultural and organizational issues often get in the way, Kugel said. “Manufacturing organizations do not use external data particularly well. They’re not necessarily using scanner data particularly well. They’re not collaborating with customers.
“There’s a general issue of sharing data between companies that involves how far do I want to open the kimono, to whom, and specifically what do I want to share downstream and upstream,” he continued. Cost and security are also factors. “You’re probably going to want to focus on a small number of partners who are significant -- your biggest suppliers and customers -- when trying to do a sales forecast and demand plan.”
Sharing manufacturing data inside an organization is no piece of cake, either. Augmenting sales and operations planning with analytics is tricky for both cultural and technical reasons, Kugel said. “When you’re in sales, you think of the account. When you’re in manufacturing, you think of the product. It’s not a trivial issue to be able to then create a data environment to be able to manage across multiple dimensions.”
Business analytics use 'immature' at most manufacturers
Ventana analyzed online questionnaires from 682 executives and managers of worldwide manufacturers to grade their companies on an analytics maturity scale, and it found that just 12% were functioning at the highest level, though manufacturing had more high performers than other industries. Kugel said maturity involves regular use of advanced techniques like predictive analytics and recognizing the need for constant data management. (SearchManufacturingERP.com and several sister sites were media sponsors and helped find participants for the study.)
Exactly half the manufacturers said some or most of their analytics data was stale or outdated, and 59% said it was only somewhat accurate. Just over a third voiced little or no confidence in the quality of the information generated by the analytics, which tends to undermine confidence in the metrics that are produced, the report warned.
While around half the respondents used business intelligence (BI) systems to produce analytics, almost all of them also used spreadsheets, which adds two days to the time it takes to provide metrics and key performance indicators (KPIs). Spreadsheets are poorly suited to complex analytics and recurring analytical and reporting tasks, the report claimed, and it advised companies to replace them with dedicated BI and analytics tools.
But that’s not to say spreadsheets can never have a role. “Companies that use spreadsheets appropriately are the ones who are innovative [in their use],” Kugel said. “The products are out there so that, in fact, the front end is Excel, but the data is in a database.”
Business and IT must form manufacturing analytics partnership
The remedy, Kugel said, is for manufacturers to get serious with a strategy that balances people, process and information issues more than it emphasizes new technology. He said companies must examine not only the data-management issues of analytics, but the processes they use to collect and disseminate data.
Half the companies don’t need to buy a single thing to use analytics more effectively.
Robert Kugel, Senior VP, Ventana Research Inc.
“Half the companies don’t need to buy a single thing to use analytics more effectively,” Kugel said. “You just have to decide to do something about it. I’m not sure the quality of the tools is as much of an issue.”
Manufacturing executives who take the time to examine BI and analytics products will probably be surprised -- and pleased -- by the state of the art, he said. “It’s important for executives in the line-of-business side to know what’s available, because it’s up to them to drive these initiatives.”
Conversely, IT managers should take it upon themselves to let the business know what’s possible, including when some requests aren’t feasible.
Problems can arise if IT isn’t respected as an equal partner in the analytics strategy. “One of the related issues is what I call the ‘tone at the top,’” Kugel said. “If people think IT is a pain in the patootie, all you’re going to wind up with is an IT department that is a pain in the patootie. Companies have the IT departments that they deserve.”
The report also advised manufacturers to assess their own maturity levels, find easy-to-use tools that support a variety of manufacturing roles and make them widely available, and consider cloud options to reduce deployment costs.
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