Imagine opening your browser and being presented with a work environment similar to that of a pilot inside a modern jet cockpit.
You are given with a carefully, and deliberately, designed visual environment designed to provide you with both the information needed to make informed decisions and controller inputs to execute them.
Like a pilot's instrument panel, you're presented with a visualization of only the most essential information to see problems as they emerge and deal with them swiftly.
Instead of moving throttles and flight controls, management decisions are sent out with a few clicks of the mouse, but a crisis is avoided, or opportunity is seized all the same.
Experts who spend their time thinking about, analyzing, and calculating metrics to gauge the performance or health of systems confront the same problem everywhere: the numbers don't mean what people think they mean.
Missing, incomplete, or out-of-date data produces misleading performance measurements, whether business KPI's or government statistics on health and education.
Even the best performance metrics are incomplete translations of ideas that defy easy measurement.
It is critically important for managers and executives to understand what a specific metric is capturing, the type and quality of data used to generate it, and why no single metric can capture 'health' or performativity.
As Peter Drucker notes, “what gets measured, gets managed” - measuring the right things, and measuring them correctly, is crucial.
Computer scientists have warned about the "Garbage in, garbage out" phenomena since the mid-1960s. In context to procurement dashboards, a well-designed front-end dashboard will produce 'junk' KPI data if it is fed incomplete, out-of-date, or incorrect data on the backend.
Customer Order and Supply Chain Cycle Times, for instance, might show a trend of slowing down if international holidays along the delivery chain aren't factored into the data.
Enterprise IT professionals and consultants have also noted problems of unintentional biases in emphasizing low quality, or incorrect, KPI's up and down the procurement chain inside firms.
At the highest level, according to The Trouble with Dashboards, "execs want the dashboards to look pretty, and they also want the data to tell a pretty story. However, the metrics worth following are often ugly." At issue is that "the most useful areas, the areas for most improvement, are generally the areas that don't look good." Lower management also tends to promote low-quality KPI's that 'look good' to their superiors.
One Size Never Fits All
Digitally mature firms that have rationalized their data and developed backend systems for dashboard frequently discover a different problem altogether.
Managing a business is not like flying an airplane for many reasons, the most important of which is that dashboards cannot be standardized like cockpits.
Executives in different industries judge their business health. Different dashboards, presenting different data and different control options, are needed even within the same firm and necessarily be customized for different users.
Managers should be presented with useful and actionable KPI’s. As already noted, this is only possible if the largely hidden back-end feeding data to generate KPI’s on the front-end dashboard is sufficiently mature.
The data presented should be carefully aligned with actionable decisions offered on the same page.
Procurement managers should be able to see invoice accounting is processing per day, performance ratios like orders approved and rejected, and see up-to-date KPIs measuring the overall health or efficiency of a business process. The need to be able to see what is in progress, who is responsible, and how operations are proceeding.
Employees, in contrast, should have dashboards that tell them what they need to be working on now and in the immediate future.
For a procurement dashboard, they can quickly pull up a table of all factories with a compliance audit expiring in the next 30 days and orders that require validation by accounting. They can see holdups in the procurement line and either perform the task needed themselves or notify someone who can.
Back-ends Matters Most
Digital dashboards, front-end user business decision interfaces, began showing up in the 1980s but were handicapped by a problem many firms face today: undeveloped backend infrastructure.
The backend could neither seamlessly transmit decisions or provide accurate and timely data to make decisions. Such business dashboards are as useless as cockpit disconnected from the engines, flaps, and instruments gathering data.
Part of the digital transformation strategy entails a process we call ‘rationalizing.’
Part of the rationalization process is having a clear vision of what type of data is needed at the front-end of the dashboard to ‘clean,’ digitalize, find, and centralize data to produce actionable metrics on dashboards.
Upper management involved in supply chains should have access to at least these seventeen KPIs on their dashboard:
- Perfect Order Measurement
- Cash to Cash Cycle Time
- Customer Order Cycle Time
- Fill Rate
- Supply Chain Cycle Time
- Inventory Days of Supply
- Freight Bill Accuracy
- Inventory Turnover
- Days of Supply (DOS)
- Inventory Turnover Ratio (ITR)
- Freight Cost Per Unit
- On Time Shipping Rate
- Turn-Earn Index (TEI)
- Gross Margin Return on Investment (GMROI)
- Inventory Velocity (IV)
- Days Sales Outstanding
- Average Payment Period for Production Materials.
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The graphic below is a network analysis showing which metrics need to be generated in the dashboard backend to produce these KPI’s.
Firm data management is a complex system in that it is interdependent and interconnected. Digital transformation means means that important data becomes digitized in interconnected clusters.
Here, for instance, we see the digitizating inventory unlocks dozens of metrics needed to calculate KPI’s. Supply chain KPIs are interdependent on other metric categories.
For instance, inventory metrics need to paired with sales data and increasingly granular time periods to produce the full list of actionable KPIs on manager’s dashboards.
Interdependency can be a source of dashboard failure when the entire firm isn’t digitizing and sharing timely data.
Important KPIs simply cannot be computed if sales is digitized and procurement is not. The upshot is that implementing interconnected dashboards throughout a firm auto-generates many of these interdependent metrics.
Digitally mature dashboard backends connect procurement, sales, and inventory processes together and auto-generate much of the data necessary to produce vital supply chain KPIs.
Don't Get Left Behind
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