How much progress has your company made toward digital transformation?
Use this 5-level framework to see how far your company has progressed toward being truly data driven.
Level 1. Do you have a unified data image?
All your information is contextualized, ensuring that:
- All decision makers have access to the right data.
- Data is easy to share and compare across your business functions and projects.
As companies improve their data-capture methods, they often find they have a tangle of incompatible data sources and formats.
Such tangles prevent organizations from using their data across multiple areas of operations, and they stall delivery of wider business benefits.
Companies must use inefficient workarounds to reformat the data manually, or by implementing additional software that further complicates their jumble of arcane datasets.
Consider a mining company as an example of Level 1 proficiency.
The company collects data from many sources that do not align. The data includes these elements and more:
- Production planning
- Topographic maps
- Telematics
- Design documents
- GIS files
- Data from sensors
- Production history
The first step is to align all these data and make them available together in a unified environment.
From there, the organization can leverage their subject-matter knowledge to create 360˚ views, enabling people in operations to draw insights from the data.
As an example of Level 1 proficiency, a manager at a mine or quarry site can make much faster decisions about how to reduce CO2 emissions to comply with corporate goals. The manager can do so without risking production goals.
If your company has achieved a similar level of data integration, you are at Level 1.
Level 2: Does your data guide effective decision making?
At Level 2, you make operational decisions from data assets and AI-based models.
You connect your high-level strategy to concrete, operational workflows powered by artificial intelligence.
Structured workflows enable you to corral massive amounts of data for effective, data-driven decisions.
Consider the situation of an inspection manager who solves maintenance issues on a power line network. She previously relied mainly on documentation, her experience in the field, and phone calls to colleagues to solve issues. She had no access to the vast combined knowledge of her organization.
But now with her company at Level 2, she has a guided workflow powered by AI. She can check predictions the AI models have made.
Then she can confirm relevant issues from the predictions. And she can validate the resolution strategies the AI models have proposed.
Such data-driven capabilities dramatically accelerate the speed and reliability of her decision making.
If your company has achieved a similar level of data-driven decision enablement, you are at Level 2.
Level 3. Does your data enable dynamic decision making?
At Level 3, you capture the results of decisions you’ve made by using AI models and workflows, and decisions are treated as data points to be analyzed and modeled for future understanding and adaptation.
For the first time, you’ll have a continuous view of whether the execution is aligned with your strategy, and, crucially, if your strategy is showing signs of success.
Your processes adapt and your models improve as more data becomes available.
You use that information to adjust your AI predictions to align with business needs.
For example, vegetation managers at an electrical utility decide whether to trim trees growing too close to powerlines.
Managers base their decisions on models showing the simulated impact of their decisions on the network, including the emerging risks of outages or wildfires, or the cost reduction achieved by postponing a given trimming operation to the next cycle.
If your company has achieved a similar level of data-driven decision enablement, you are at Level 3.
Are you there yet?
Level 4. Have you expanded your data-driven decision capabilities across business functions, operations, and geographies?
A level 4, your organization has moved beyond optimizing local, individual decisions. You connect to a global decision network.
Decisions affect each other across the business — and sometimes across industries.
The workflow for managing power line inspection in electrical utilities offers a good example.
Alteia’s software creates a network of organizations and individuals who can all work from a single source of truth.
Decision makers can see the effects of their decisions on other areas of the business.
They can understand complex cost-benefit tradeoffs.
At Level 4, infrastructure managers at an electrical utility can correlate household electricity consumption to decisions made by its vegetation inspection team.
They can use the insights from the correlation to evaluate investment decisions, work plans, and capital allocation plans for the next 5 years.
If your company has achieved a similar level of data-driven decision enablement, you are at Level 4.
Are you there yet?
Level 5. Are your operations driven by AI models?
At Level 5, you have broad and deep digital data that provides current, in-depth knowledge across your operations. You’ve established continuous, iterative processes that constantly capture and analyze new data.
Your processes then aggregate, mine, model, and visualize the data to provide a steady flow of valuable insights. These ‘data loops’ enable your models to accelerate decision making autonomously.
You’ve refined your models and trust their efficiency, but your data no longer delivers value mainly by enabling better decisions. So now you can connect your models directly to your operational infrastructure to control execution.
For example, an electrical utility uses their AI model to send work orders directly to tree-trimming contractors, and the contractors then trim vegetation that grows too close to the utility’s powerlines.
The entire process occurs without human involvement.
Human operators continue to monitor the network and control the parameters, but they intervene only when it’s a good use of their time and expertise to do so.
You focus your company’s human attention where it can add the most value.
If your company has reached a similar level of data-driven decision making and execution, you are at Level 5.
Are you there yet?