Whether a small project or a large transformation program, how well an organization manages the human side of change dictates—to a considerable extent—the pace of adoption and how much employees and the organization benefit from the change.
Manufacturers today are at an evolutionary fork in the road. They must transform into data-driven enterprises to stay relevant and navigate constantly changing market realities. At the heart of this transformation is fostering a data-first culture. However, many organizations find this one of the most challenging hurdles to clear.
Why is organizational culture so important?
An organization’s culture can “make or break” its transformation into a data-driven enterprise. This is because becoming data-driven is, first and foremost, about people. Not only are people central to all the foundational aspects of building a data-driven enterprise: data governance, architecture, security, etc., but they also must be equipped with the tools, processes and training to use data in their daily work and to make decisions. The 2023 Voice of Our Clients research reveals that 57% of manufacturing executives identify culture and change management as the top constraint to achieving their business priorities.
There are two key reasons culture is pivotal to success:
- Certain cultural norms better position an organization for innovation, faster learning and change adoption.
- By developing cultures associated with the best places to work, organizations can attract and retain data talent—currently a top challenge in manufacturing.
Fostering a data-focused culture
A data-first culture prioritizes data collection, analysis and utilization across an organization. In a data-first culture, data is viewed as a strategic asset that can provide valuable insights into customer behavior, market trends, and overall business performance. IDC research shows that organizations benefit from the full value of data only when they have data-first culture. To build a strong data culture, leaders must develop a vision for the ideal culture and apply a structured change management approach to achieve this vision. According to the Humans Synergistics culture model, there are several facets to creating the ideal culture, including fostering a “constructive” culture1.
A constructive culture has several key features that enable faster and better transformation to a data-driven enterprise:
- Achievement - Employees are encouraged to take on challenging tasks with realistic goals and gain a sense of accomplishment from overcoming them.
- Self-actualizing – Employees focus on growing professionally and personally and taking on new and interesting activities.
- Humanistic-Encouraging – Employees are involved in decisions that affect them and receive support to advance their growth and development.
- Affiliative – Employees feel valued and are enabled to thrive in a positive environment. They cooperate and collaborate with others and treat people as more important than things.
For data-driven transformation to succeed, manufacturers must strive to build an innovation culture where asking questions, seeking feedback, experimenting, reflecting on results, and openly discussing mistakes are encouraged. Innovative cultures discourage aggressive-defensive behaviors such as criticism and perfectionism, which make transformation more challenging.
How can manufacturers start building a data-focused organization?
Manufacturers face several challenges in transforming into a data-driven enterprise. Based on conversations with manufacturing clients across sectors, here’s a list of the key difficulties and our recommendations to overcome them.
- Unconvinced/unaligned leaders – Leaders need to develop a data-first vision, which is the starting point of transformation. In many cases, leaders themselves may not be convinced of the need to become data-driven and, consequently, are not supportive of a data-first vision. In addition, there may be a lack of alignment between business and IT executives in supporting and executing the strategy.
Action: Leaders must align and lead the change, starting with understanding the value of data and prioritizing a data-driven approach. Develop a shared vision and roadmap by aligning executives across the organization and communicating the plan to all employees. Encourage employees to use data to help identify patterns, predict future trends, and make informed decisions to improve manufacturing processes.
- Cultural impediments – In manufacturing, existing cultural norms, attitudes or biases tend to prioritize intuition, experience or hierarchy over data-driven decision-making.
Action: Understand the current culture so that you can assess, amend and adopt the type of culture needed to better position the organization to become data-centric.
- Siloed organizations – One of the fundamental tenets of a data-driven organization is data-sharing. Traditionally, manufacturing organizations are structured in a hierarchical way that favors specialization and top-down decision-making and information flow. This can breed information silos and impede the collaboration needed across teams for developing data infrastructure and governance.
Action: Encourage data sharing and collaboration by breaking down silos, building cross-functional teams that work together on data analysis projects, and encouraging employees to share their data findings and learn from each other.
- Skill gaps – Research from the Journal of Manufacturing Systems estimates that the manufacturing sector has the third-highest demand for data analytics roles, only behind the professional services and finance sectors. The demand for data science skills is evidenced by the number of manufacturing job postings growing 82% over the past four years. In the future, manufacturing jobs will require employees to master a portfolio of core manufacturing science and technology skills, domain knowledge and computational skills associated with data science. Hiring talent poses a significant challenge for manufacturers, resulting in a lack of data-skilled employees to collect, analyze and use data for decision-making effectively. Often, there is also a lack of a vision of the talent and expertise needed to be a truly data-driven enterprise.
Action: Start by defining the roles/jobs and profiles needed for the future, perform skill gap assessments for the entire organization and specific departments, and then implement upskilling programs, such as apprenticeships, internships and train-to-hire programs, and update job descriptions. Employees must be proficient in traditional manufacturing technologies and have knowledge of advanced data-rich computer-automated technologies. To retain and attract new talent, develop a culture that offers employees a career with a future-driven purpose.
- Slow buy-in and adoption – Successful transformational change relies on buy-in and adoption across all levels of the organization. Instilling a data-first culture requires significant changes in processes, workflows and decision-making approaches. Employees who may fear new skill set requirements or do not understand the “why” can resist adopting a data-driven approach.
Action: Creating an adaptive and data-first organization requires human-centered design and cultural transformation approaches. Draw up and implement excellent change management strategies to prepare employees for the transition. Start with engaging employees in shaping new initiatives and the future vision. Also, focus on clear communication and training so that employees know the “why” and “how” of the transformation and can become the champions of change.
Whichever stage of data-driven transformation an organization is currently in, it is possible to implement, fortify or course-correct the approach with the above points in mind to ensure people are at the core of the transformation.
1 OCI® style names and descriptions are from Robert A. Cooke, Ph.D. and J. Clayton Lafferty, Ph.D., Organizational Culture Inventory®, Human Synergistics International, Plymouth, MI. Copyright © 2023. All Rights Reserved. Used with permission.