In manufacturing, most companies grow through acquisition. Although this is great for expanding the business, it can make some core data-management tasks unusually tough. Organizations typically start by supporting manufacturing operations at a single location. Whatever data management tools are necessary—enterprise resource planning systems (ERPs), procurement systems, different databases—tend to work well for controlling information within each system. The problems begin once the organization establishes multiple locations, each of which has several databases, IT systems and ERPs. The complexity increases when numerous product lines or geographies are involved, as they all bring their own assortment of data-management solutions that are unique to their specific location.
This level of decentralization may have been desirable in the past, but today, most manufacturers want to take advantage of their scale and therefore need the ability to access more centralized data, even if the operations themselves remain decentralized. Yet, without a holistic view of data, senior management is incapable of getting insight into these fragmented systems to determine when these silos impede agility. Examples include understanding what next month’s entire expenses for product development are or deciding how the organization can respond to unplanned business conditions like the Coronavirus disease (COVID-19) pandemic. Many manufacturers are asking these questions today, but if they can’t find a way to master data to get the insights and agility they need, staying operational—let alone competitive—will be an even bigger challenge.
The quest for data reliability starts by understanding the hidden costs of fragmented data
The manufacturing issue no one wants to deal with is the data fragmentation that stems from multiple IT systems. It’s not uncommon for manufacturers to use several ERPs, especially across various data dimensions and sites. The ensuing “ERP sprawl” is worsened by a similar state of upstream data sources such as customer relationship management (CRM) and procurement systems, all of which make it extremely difficult to get comprehensive insight into business concerns. This fragmentation delivers different versions of the truth, none of which are comprehensive or complete. This means any attempts to aggregate this information for company-wide decision-making is sure to yield inaccuracies, inconsistencies, redundancies and delays.
Gaining visibility into an organization’s data has always been formidable in the manufacturing industry, where companies have a universal need to generate data-driven insights for enterprise agility. Whether looking to improve global business operations, optimize supply chains and/or boost margins, most manufacturers’ data is hopelessly fragmented across multiple ERP tools, geographies and organizations. Complicated by numerous upstream systems and the trend of consolidation, the resulting ERP sprawl is prolonging the time it takes for the business to make informed decisions to drive growth and improve operations. Effective operations require insights and agility that manufacturers can’t get because of these silos. Most organizations implement ERP systems to leverage data as an enterprise asset, but in reality, it’s a liability preventing the very things it should enable.
Manufacturers also require visibility, not just into individual product lines or locations, but throughout their entire operations. They need metrics across the supply chain, customers, internal operations and more to know which actions optimize efficiency and productivity. However, this is nearly impossible to gauge if they don’t have accurate, timely and complete data about their business processes. Poorly governed information silos compromise overall productivity and escalate costs. Even something as basic as gaining insight into current or future employee needs for human resource planning is impaired by this lack of visibility, creating production lulls or overspend.
Common methods to data management -- too hot, too cold or just right?
Something must be done to make good on data’s promise and overcome its fragmented landscape and lack of visibility, but what are the alternatives? There are three common approaches considered to solve this problem that typically involve manual methods, ERP consolidation and master data management (MDM).
1. The manual approach.
This style involves the typical knee-jerk reaction organizations take to solve this issue by doing everything themselves. It consists of hiring more people, using more spreadsheets and stitching data together by hand across numerous tools, IT systems, business domains and use cases. Once that’s accomplished, the business still has the unenviable task of repeating this process every time business requirements, data sources or the data itself changes, giving them no chance of keeping up.
The sole positive of this approach is it’s usually what the company’s been doing for years. Organizations can start immediately, or simply continue what they’ve been doing, and know exactly how to do it. But, as most manufacturers can attest, the practicalities of this method completely undermine its benefits. Chances are the organization knows firsthand how labor-intensive, costly (especially with the new hires), error-prone, non-scalable and endlessly repetitious this cycle is. This leads most manufacturers to explore an automated approach.
2. Consolidating ERPs.
Another popular approach is to consider standardizing all siloed systems into a single, large ERP solution or leverage a few ERPs using a single vendor. This solution would appear to be comprehensive enough to resolve the problem and certainly rectifies the data sprawl issue. But, those who try soon realize its principal drawbacks, it’s far too pricy and takes too long to finish.
The different domains, sites and manufacturing locations usually have varying requirements, so attempting to consolidate many ERPs is a major business disruption that prevents these individual units from doing their jobs. Consequently, this approach increases department factionalism, company politics and is unlikely to ever get done. If so, it takes years, which businesses aren’t promised in today’s era of COVID-19.
3. Master data management.
Gartner defines MDM as a technology-enabled business discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, governance, semantic consistency and accountability of an enterprise’s official shared master data assets. MDM is becoming a viable alternative for manufacturers for several reasons. Its automation advantages quickly rectify the drawbacks of the manual approach. These hubs also help automate and accelerate the fundamentals of data quality, data governance and record matching necessary for insight across systems. Once this manual work is done, it’s stored in the MDM and quickly applied to future use cases.
Also, MDM allows organizations to combine data sources to create a golden record without company politics bogging down the implementation, unlike the ERP consolidation method. The result is a master set of reference data for slow-moving manufacturing data related to domains like customer, product, supply chain and more. Better yet, these often become the basis of common references, even across domains in competitive offerings, for implementing governance standards across systems. Finally, manufacturers are finding that MDM solutions are much less invasive than consolidating ERPs because MDM lets the organization leave existing systems in place, so business units aren’t interrupted.
Cutting through disparate data and linking together information that delivers actionable insights into the full supply chain is not an easy process and to be clear, MDM is not magic. There are cost considerations and set up work that has to be done before manufacturers can start reaping its benefits. However, the length of time to prepare data is nothing compared to how long it takes to consolidate ERPs, just as the speediness of its automation outmatches the time it takes manufacturers to manually stitch together data. As most manufacturers struggle to stay competitive, they find that MDM is more affordable than yet another ERP investment, and certainly more so than hiring a group of employees to create even more spreadsheets. MDM is not too hot, not too cold, but just right for actionable insights and agility.
