Increase Your Data Readiness

To use data, it needs to be collected and visualized so that it is meaningful to users. Being data-ready to manage operational metrics involves ensuring that you have the necessary data and infrastructure in place to effectively measure and track metrics related to your operational processes.

Consider these key questions:

Does the data you require currently exist?
Are you able to collect the data in a way that can allow for the reporting you require?
Does the data collection cadence allow for reporting that supports decision making, or is the data only allowing for historical insights?
Who owns the data?

While manual data pulls and reports can in some cases be created, it is strongly advised to implement technology to support these efforts to encourage accuracy and timeliness. Consider the different phases of digital transformation and your current maturity level within these phases.

The data phase is where data is centralized to one location. Identify the relevant data sources (project management tool, asset management system, financial systems, etc.) where the data for your metrics lives. It is recommended to select a centralized data platform, and the good news is that often operational data is or can be obtained through project management tools. Plans for data integration and governance will need to be considered.

In the analytics phase, raw data is analyzed to identify trends. If available, you can use historical data to analyze cause and effect of past results which can help to develop predictive logic. The logic is that if you can understand past results and anticipate future trends, you can optimize the process. Consider how useful this type of analysis would be for managing capacity and utilization.

The translation of analytics into insights and delivering to the right people at the right time happens in the insights phase. In this phase the aim is to deliver real-time, continuous feedback on the insights to the data end users. Developing an insight delivery engine to share insights in a fast and effective way to those who need them will reduce communication friction across the organization.

The final phase of digital transform is the agility phase where company culture is built to empower people to use data to succeed. This involves making efforts to seamlessly connect the data to people to encourage information sharing and creating the expectation of collaboration and ownership:

Implement networked decision making, where it is distributed among a network of individuals who have different perspectives, expertise and responsibilities related to the project.
Create omnidirectional insights flow through by creating a centralized repository of best practices, knowledge and resources that can be easily accessed and shared by everyone in the organization. This repository can include key information on project management, brand and creative guidelines, briefs, technical specifications and other relevant information.
Create learning feedback loop mechanisms (i.e., project retrospectives).
Develop a shared consciousness where each team sends feedback to each other ensuring all sides are aware and learn from each other.
Foster empowered execution where those closest to the problem have the authority to use insights to make data-driven decisions in real time.

Knowing your current level of data readiness will allow you to consider any resources required to increase the data collection, reporting and analytics efforts. Understanding these requirements will start to clarify the type of roles that need to be considered (example: data scientist, analyst, data engineer or architect) as well as the system requirements. This information will guide the development on a roadmap to achieving higher metric strategy maturity.

When considering a metric strategy, you want to be extremely thoughtful and think long-term. You do not want to be in a position where you need to overhaul your measures every few years because that will result in losing very important historical data that has meaning and can be used for comparisons and baselines.

For operations leaders who are looking to increase their Operational Metric Maturity, it is recommended you develop a comprehensive metrics strategy by identifying what matters most to your organization, defining operational performance indicators and metrics that ladder up to that top-down direction, identify and consult your data end users and assess your data readiness. Once you understand your current level of maturity, you will need to determine where you should be and a roadmap to develop and achieve maturity.

When considering a metric strategy, you want to be extremely thoughtful and think long-term. You do not want to be in a position where you need to overhaul your measures every few years.