The manufacturing industry has hit a data crisis. Today, manufacturing companies struggle to manage, integrate and make sense of all their data as it stems from a plethora of functional groups and technology applications. For example, an ERP system may be leveraged by the finance department to create the annual operating plan or by the procurement team to buy raw material. There may also be offline sources that are used by sales and marketing teams to provide budgetary and promotional information. There is a variety of data coming in from multiple sources, so how can manufacturers consolidate and analyze all this data to enhance efficiency and improve the overall business?
Although in recent years some manufacturers have incorporated Sales & Operations Planning (S&OP) processes to help collaborate across functional areas and drive strategic planning, a significant data gap still exists. As a result, manufacturers continue to struggle with an array of business problems, including:
- Attracting talent — there is a negative perception of the manufacturing world, and many young professionals no longer see it as a potential career path.
- Managing a global supply chain — each country has its own socioeconomic struggles and one country’s political unrest could severely stifle a manufacturer’s supply chain if not addressed correctly.
- Asset Management — many machines are seen across a shop floor in each plant and can lead to excessive downtime when not managed appropriately.
Having easy access to data can help manufacturers resolve these issues, but proper data management is still a dilemma and can be attributed to a lack of data governance. According to a study by the Economist Intelligence Unit, only 42 percent of manufacturers have a well-defined data-management strategy in place.
If manufacturers want to create a data-driven organization, they should consider these six steps to help jumpstart their data governance framework.
Align. Alignment starts by understanding the manufacturing landscape. Manufacturers must consider the organization’s business strategy and determine what approach works best alongside the organizational culture. While beginning to consider how to best structure the data governance framework, manufacturers should engage key stakeholders across the organization, which may include individuals from the core S&OP team or employees on the shop floor.
Appeal. Promoting the opportunities and business benefits that will stem from a data governance framework is critical for gaining adoption. Highlighting some of the intended business goals (e.g. reduced downtime due to machinery issues) through a heightened sense of urgency will help answer the most important question about the initiative — “What’s in it for me and why is it important?”
Engage. Stakeholders from across the organization will need to be engaged in the data governance initiative to ensure it is sustainable and effective. Organizations should engage the right stakeholders at a leadership level, but should also consider establishing a change network of individuals across the broader organization — including shop floor personnel to help share key messages. These individuals within the change network will help build momentum and can also serve as an initial sounding board when attempting to operationalize critical processes.
Act. Define data governance processes and begin initiating prioritized data requests. Organizations can establish a team of data stewards or a separate subcommittee to help execute the initiative. As they uncover data discrepancies and inconsistencies (which may appear once specific data is integrated across plants), organizations should consider instituting master data management and data quality management processes and tools.
Unite. Make sure leaders, data stewards and subcommittees that support the data governance initiatives meet on a regular basis to ensure progress is being made on each data initiative. To unite the broader organization in their ability to support the changing processes, hold training programs for the respective stakeholders. The frequency and approach to meetings should vary depending on the size and complexity of each group. For example, it might make sense to facilitate a data governance meeting at each plant location once a week, and hold an overarching meeting with executive leadership on a monthly basis.
Convey. Make sure to communicate the results of data initiatives supported by the data governance committee first with engaged stakeholders and then with the broader organization. It’s important to showcase meaningful reports and dashboards to articulate the impact. Engage the change network in the communication process by allowing them to deliver some of these messages. Although this step is presented last, communication should be shared throughout the entire data governance journey.
Effective data management and analysis is becoming an urgent imperative for manufacturers. Data governance allows organizations to identify data opportunities that align with their business strategy, prioritize data initiatives and ultimately, provide a central point for management of all significant data discrepancies. If manufacturers want to keep their diverse data portfolio in check, they will need to implement a data governance framework.
Mike Hughes and Gordana Radmilovic are both with West Monroe Partners.