If you're not measuring the impact of digitalization on your business, you're not digitalizing properly. Here's how to start.
What metrics should engineers track to demonstrate that an investment in digital transformation is delivering business results?
There are many quantifiable measurements that can assess performance, track progress, and measure the success of a digitally transforming business. The twelve categories below are all good starting points for engineers to determine what metrics will serve them best—and how to tell if a metric is truly valuable or merely a distraction.
Product quality
Digital transformation supports improving product quality by supplying the required digital production data. Example quality metrics include trends for monthly or quarterly:
- Number of units produced that require rework per thousand units produced
- Number of quality issues identified by quality assurance tasks per thousand units produced
- Number and cost of warranty claims as a percentage of unit and sales value
- Number and cost to settle lawsuits alleging product defects as a percentage of sales
Manufacturing
Digital transformation supports improving product quality by supplying the required summarized Industrial Internet of Things (IIoT) data from manufacturing plants. Example manufacturing metrics include trends in monthly or quarterly:
- Average number of products produced per production hour
- Number and hours of unscheduled downtime by machine
- Product scrap rates per thousand units produced.
- Consumables used per thousand units produced
Supply chain
Digital transformation supports improving the supply chain by aggregating the required digital data from the many external vendors involved. Example supply chain metrics include trends in the monthly or quarterly number of:
- Excessive shipping times per thousand shipments from the production location to a store or consumption plant
- Average daily out-of-stock items
- Average daily number of items marked down for sale
- Returned shipments due to incorrect products or quantities per thousand shipments
- Variance in accuracy and timeliness of shipments by vendor
Innovation
Digital transformation supports innovation by searching external data sources for ideas, competitor information and technology developments. Example innovation metrics include trends in monthly or quarterly number of:
- Ideas evaluated
- Experiments conducted or prototypes built and evaluated
- Product market tests conducted
- Patents filed
Operating cost
Digital transformation contributes to reducing operating costs in many companies by identifying cost-reduction opportunities. Example cost metrics include trends in monthly or quarterly operating costs:
- In aggregate, by product line or geographic area
- Change
- Variance compared to the same period in a prior year
- Comparison by plant or store
Cycle times
Digital transformation supports reduced cycle times by modeling the impact of business process alternatives. Example cycle time metrics include trends in monthly or quarterly:
- Number of business processes revised
- Estimates of staff effort hours saved as a percentage of hours worked
- Estimates of machine hours saved as a percentage of active machine hours
- Estimates of defect reduction or quality improvement
Data driven decision making
Digital transformation reinforces data driven decision making by supplying the required digital data. Example decision making metrics include trends in:
- Percentage of management and operational decisions made primarily with data rather than based on experience or expertise
- Number of disasters or high-risk situations avoided
- Number of unanticipated opportunities pursued based on previously inaccessible data
Data quality
Digital transformation supports improving data quality by identifying errors and anomalies. Example data quality metrics include trends in:
- Average daily effort hours spent on data cleaning
- Percent of data columns, tracked for data quality, meeting established targets
- Number of products requiring rework due to missing or inaccurate data in manufacturing per thousand units produced
- Number of shipments requiring correction due to data confusion in distribution per thousand shipments
- Returned shipments due to missing or incorrect shipping data per thousand shipments
Revenue
Frequently, digital transformation contributes to increasing net revenue by identifying new customers and markets. Example revenue metrics include trends in monthly or quarterly revenue:
- In aggregate, by product line, geographic area, or new customers
- In number of items per sale
- Growth
- Variance compared to the same period in a prior year
- Comparison by plant or store
Customer satisfaction
Digital transformation improves understanding of customer satisfaction by integrating the required data from various internal sources. Example customer satisfaction metrics include trends in monthly or quarterly:
- Number and duration of call center interactions
- Average daily website and smartphone app session lengths and number of pages viewed
- Number of abandoned e-commerce shopping carts as a percentage of sales completed
- Product return rate per thousand completed sales
- Number of customer complaints and negative online reviews per thousand completed sales
Business plan
Digital transformation contributes to improving the business plan through scenario planning. Example business plan metrics include trends and forecasts in:
- Net income, gross margin, return on capital, outstanding debt or dividends paid
- Market share by product line
- Time-to-market reductions for product launches or territory expansions
- Business plan progress compared to competitors
Capital investment efficiency
Digital transformation improves capital investment efficiency by identifying cost-reduction opportunities through simulations. Capital investment efficiency is often measured as net revenue or units of production divided by capital employed. Example capital investment metrics include trends and forecasts for monthly or quarterly:
- Corporate capital investment efficiency
- Capital investment efficiency comparison by plant
- Capital investment efficiency changes compared to the same period in a prior year
- Modeling the use of debt and equity
How to choose the right success metrics
Valuable types of success metrics include:
- Trends and variances that provide an instant picture of the situation
- Comparative metrics across similar periods or facilities
- Metrics involving division to calculate performance per unit of time or capacity
Types of metrics to avoid include:
- Simple activity and point-in-time metrics, which are not typically helpful for decision-making
- Lagging metrics that are too late for effective interventions
- Indices, which are typically too complicated to calculate and can be difficult to understand
- Modeled metrics, which come with error terms and are therefore helpful for planning, but not practical for operational intervention
Superior success metrics exhibit many of the following characteristics:
- Derived from the goals of the business plan
- Aligned with the strategies being performed to achieve the business plan
- Specific to be easily understood by the target audience
- Easily measurable with low effort and consistent quality
- Actionable so that employees will know what corrective actions to take to improve performance
- Indicative of future business performance
- Contextualized by budgets, targets, or widely accepted industry benchmarks
- Reliable in that they are accurately calculated and not revised after publication
- Consistently reported and infrequently modified
- Timely to support rapid intervention
Digital transformation delivers the digital data to produce the success metrics organizations monitor to drive business improvement.
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Yogi Schulz has over 40 years of Information Technology experience in various industries. He writes for ITWorldCanada and other trade publications. Yogi works extensively in the petroleum industry to select and implement financial, production revenue accounting, land & contracts, and geotechnical systems. He manages projects that arise from changes in business requirements, from the need to leverage technology opportunities and from mergers. His specialties include IT strategy, web strategy, and systems project management.
