To begin, organizations need to have a destination in mind. Author Andy Stanley once said, “the greatest motivator of change is a crystal-clear vision of what the future should look like”. By communicating this destination broadly across the organization, everyone can understand the purpose and direction of the data-driven culture and work together to achieve it.
This series reviews the ten things an organization can do to implement a data driven culture. Let’s begin...
#1 Identifying a Model or Framework
One of the challenges of developing a data driven culture is to identify a model or framework that suits the organization's goals, needs, and capabilities. There is no one-size-fits-all solution, as different organizations may have different data sources, systems, processes, and stakeholders. These models and frameworks can provide guidance, best practices, and benchmarks for organizations to assess their current state, identify gaps and opportunities, and plan their actions and improvements.
When identifying a model or framework, it is important to ensure it incorporates your organization's values and may not always be the ones that you can easily find on Google. Take for example, the Shingo model. This model utilizes guiding principles that shape an organizational culture by influencing the interactions between its systems, tools, and results. An organization's foundation should be built on a culture of respect, with leaders who lead effectively. Once this is established, the team should be equipped with the necessary tools to drive improvement. By aligning the work with the organization's goals and successfully implementing these three elements, positive results will follow. This is a powerful model that helps to guide an organizational culture. Additionally, accrediting bodies that focus on an evidence-based data driven care model can be used as a model or framework. The Commission on the Accreditation of Rehabilitation Facilities evaluates organizations based on their ability to use data to enhance the patient's experience. If an organization does not meet its targets, an action plan must be implemented to address the issue. This emphasizes the significance of managing, analyzing, and responding to data, a core tenet of any data driven culture.
Whatever model is chosen, it should align throughout the system and be used as a guide in the journey towards a data-driven culture. This will help to ensure that the model is effective and that it is embraced by all members of the organization.
#2 Understanding Data Needs
One of the biggest challenges in developing a data driven culture is understanding data needs. While an organization can collect vast amounts of data, it is important to determine what data is relevant and necessary to collect. This involves considering data requirements from various sources, including regulatory and accrediting bodies, publicly reported websites, and patient safety organizations. To determine what data to collect, an organization must consider its goals and needs, such as compliance, competitiveness, and meeting standards. It is important to ask what data is relevant to the work that needs to be completed.
In addition to considering external data requirements, it is also important for organizations to assess their internal data needs. This involves identifying key performance indicators and metrics that are relevant to the organization's goals and objectives. By collecting and analyzing this data, organizations can gain valuable insights into their performance and identify areas for improvement. It is also important to regularly review, and update data needs to ensure that the data being collected remains relevant and useful.
A central data repository can be a powerful tool for managing data requirements. By creating a single source of truth, organizations can ensure that all members have access to the same, accurate information. This can help to reduce errors and inconsistencies and can also save time and effort by eliminating the need for multiple spreadsheets and files. Additionally, a central data repository can help to improve data governance, by providing a clear and transparent record of all data elements and their sources.
To ensure that data is collected consistently, it is important to create a data guide. This guide should define the data elements used to guide a program and document the cadence at which data is collected. It should also clearly outline who is accountable for each aspect of data collection, management, and analysis. By creating a comprehensive data guide, organizations can ensure that data is collected in a consistent and standardized manner, reducing the risk of errors and inconsistencies.
#3 Understanding Data Problems
A crucial step in fostering a data-driven culture is comprehending the data-related issues that an organization wants to address or resolve. Instead of just inquiring about data skills, quality, metrics, and staff attitudes, it's essential to begin with the question of why. As motivational speaker Simon Sinek puts it, “when we know why we do what we do, everything falls into place.” Consider the significance of the problem and its impact on the organization. For many organizations, their pillars of excellence or mission/vision/values provide sufficient motivation. Sometimes, it's simply the right thing to do. Whatever the reason, it's vital that front-line leaders grasp and can convey it to their staff. When cultivating a data-driven culture, leaders must be transparent with their staff about the objectives. Staff must understand the importance of these objectives to the company, their team, and themselves. Front-line staff need to know the benefits of participating in this effort. This will engage them and foster a data-driven culture.
Once an organization understands the importance of a data problem, they need to employ tools such as data visualization and statistical analysis to comprehend the issue and identify data trends. Leaders should have a toolbox of continuous improvement tools, including 5 Whys, fishbone analysis, root cause analysis, Gemba walks, process mapping, and pareto charts, to help them understand their data problems. These tools will aid organizations in identifying the root cause of the problem and developing a data-driven solution. In addition to using these tools, it is also important for organizations to foster a culture of collaboration and communication. By encouraging open and honest dialogue, organizations can ensure that all members have a voice and can contribute to the problem-solving process. This can help to identify and address any underlying issues or concerns and can also help to build trust and buy-in among staff. By working together, organizations can develop more effective and sustainable solutions to their data problems.
Conclusion
Developing a data driven culture is not a one-time project, but a continuous journey that requires constant learning, adaptation, and improvement. To harness the power of data, organizations must identify a suitable model or framework, comprehend their data requirements, and understand their data-related issues. By doing so, they can gain valuable insights, opportunities, and advantages that can aid in the development of a data-driven culture. In the next newsletter, we will discuss how organizations can prioritize what is important, establish an organized approach to process improvement, and make data comprehensible to foster a data-driven culture
References:
Shingo Model: https://shingo.org/shingo-model/