Instrumentation · Reference
The bodies of work that govern how a quantity is drawn honestly, and how a screen lets an operator find the one thing that is wrong. A reading list for building instruments, not more dashboards.
The premise
A Master Production Scheduler should be reasoning about a decision. Instead they are doing the work a system was supposed to do — carrying numbers between screens by hand.
Watch a scheduler at a partial-shipment call and the pattern is unmistakable. The same ERP is open in several browser windows, each holding tabs on a different screen — supply, the supplier scorecard, open orders, inbound logistics. Alongside it sit a planning system and a freight rate sheet. To weigh a single trade-off — accept a short shipment from one supplier because a second will over-ship the same part at a different landed cost — they reach across three systems and reconcile the numbers in their head. The machine that was meant to integrate the data has quietly delegated that job to the person.
The cost is not only time. Every switch between windows carries a reorientation tax — where was I, what did that number mean, which order am I on — and the tax compounds until the human working memory is spent on plumbing rather than judgment. On some desks the toggling is heavy enough that the machine itself has to be rebooted to recover. This is not a training problem or a discipline problem. It is a design problem, and it has a settled body of knowledge behind it.
A dashboard answers “what are all the numbers?” An instrument answers “what do I do now?” A cockpit and a fire-truck pump panel are the models, not another wall of tiles.
The A2go answer is a notebook: a page assembled around one decision, where the related customers, suppliers, and SKUs stay fixed while the telemetry on the page changes to the operator’s need — not to a row of slicers and filters. The page is interactive, it persists, and it archives once the decision is made, so the reasoning behind the call is kept, not thrown away. Building that well means standing on two literatures at once: the craft of drawing a quantity honestly, and the human-factors discipline of the operator’s screen. What follows is the reference list for both, plus the supply-chain framework that says which quantities are worth instrumenting.
Part I · Drawing the quantity honestly
The primary sources on how a reader decodes a chart, and the discipline of putting the most accurate visual channels on the most important quantities.
Edward Tufte
The data-ink ratio, small multiples, sparklines, and the lie factor — the argument for removing everything on a chart that does not carry information.
William S. Cleveland
Graphical perception established by experiment: the accuracy hierarchy of position, length, angle, then area — and why a dot plot is read more accurately than a bar.
Jacques Bertin
The foundational grammar of the retinal variables — position, size, shape, value, color, orientation, texture — and the first systematic theory of what a mark can encode.
Leland Wilkinson
The formal system beneath ggplot2, Vega-Lite, and Observable Plot — the reason a chart is a set of mappings rather than a fixed picture type.
Tamara Munzner
The modern academic backbone: a what–why–how framework for matching a visual encoding to a task. The bridge from perception research to practical design.
Stephen Few
The practitioner’s rulebook for tables, graphs, and single-screen displays — and, in Signal, the discipline of separating a real signal from ordinary noise.
Part II · Choosing the form, communicating the finding
The references that pick the form from the data relationship, and the ones that carry a finding to a decision-maker without distortion.
Financial Times · Graphics desk
Over forty chart types organised by the relationship in the data — deviation, correlation, ranking, distribution, change over time, part-to-whole, magnitude, spatial, and flow. Identify the relationship first, then let it choose the form. The single most useful guide for choosing a chart, as a poster and an interactive.
Alberto Cairo
Information graphics as a functional tool for reasoning, with a working standard for truthfulness — and a field guide to the ways a chart misleads, on purpose or by accident.
Cole Nussbaumer Knaflic
The business-communication standard: strip the clutter, direct attention deliberately, and let the chart make one point. The most practical bridge from analysis to an audience.
Datawrapper · Lisa Charlotte Muth
The best living, worked reference on color, chart choice, and annotation — short, evidence-led essays that translate the canon into decisions you make in an afternoon.
Part III · The statistical-publishing standard
The tradition of statistical agencies and business-reporting standards — where a figure carries its source, its units, and its revision date as part of the chart, not beside it.
Jonathan Schwabish
Written by a government economist for analytical communication — the closest match to a statistical-agency standard, and the same lineage a BLS or Bernan reader will recognise.
Urban Institute
A living, open style guide: color with fixed meaning, mandatory titles, source lines, and units, and WCAG-AA contrast. A model for a house standard that holds without constant effort.
European Commission · Eurostat
The public-statistics rulebook for official figures — chart choice, accessible color, and the provenance conventions that make an agency’s numbers auditable.
IBCS Association
A SUCCESS-framed notation for consistent business and financial reporting — the same variance scaled the same way every time, so a number means one thing across a company.
Lineage note — this section reflects the statistical-publishing tradition of the U.S. Bureau of Labor Statistics and the reference-publishing standards of Bernan: a figure is not finished until its units, seasonal adjustment, source, and revision date travel with it.
Part IV · The operator’s screen
The cockpit, the control room, and the pump panel — the discipline of designing a screen so an operator can find the one item about to fail, out of thousands, in about a second.
International Society of Automation
The standard that codifies High Performance HMI: a good operating screen is mostly neutral gray, and a color appearing is itself the alarm. It defines the HMI lifecycle — a frozen style guide of palette, symbols, and naming, then a display hierarchy, then build, operate, and management-of-change. This is the industrial-control answer to exactly the toggle-and-overload problem the premise describes.
Hollifield, Oliver, Nimmo & Habibi
The practitioner’s companion to ISA-101: how to assess, design, and implement control screens that raise an operator’s reaction time by showing only what matters and removing the rest.
Kim Vicente & Jens Rasmussen
The framework, from Risø National Laboratory, for interfaces that support knowledge workers under novelty — mapping the skills-rules-knowledge levels so the display carries the work domain, not just its readouts.
Mica R. Endsley
The canonical model of situation awareness — perceive, comprehend, project — and design that supports it. Most human error traces to an SA failure while integrating information from many sources: precisely the scheduler’s task.
Donald A. Norman
Affordances, signifiers, mapping, and feedback — the vocabulary for why a control is obvious or baffling. The foundation under every screen that expects a human to act on it.
ASM Consortium (Honeywell-led)
Decades of research on how operators lose and regain control of complex plants, and the display and alarm practices that keep the abnormal situation legible instead of drowning it in data.
Part V · What to instrument
The domain layer decides which quantities are worth a channel at all. ASCM’s SCOR Digital Standard supplies the shared vocabulary of processes and metrics behind an A2go notebook.
ASCM · Association for Supply Chain Management
The cross-industry reference model for supply-chain processes — Orchestrate, Plan, Order, Source, Transform, Fulfill, and Return — with a hierarchy of more than 250 metrics whose lower levels diagnose the higher ones. It is the map that tells a notebook which telemetry belongs to a decision, and what “good” means for it. A2go references SCOR as ASCM’s framework; the company’s founders contributed to SCOR as practitioners at PRTM.
Reliability · Responsiveness · Agility · Cost · Profit · Assets · Environmental · Social
The attribute set behind every metric code — customer-facing resilience (RL, RS, AG) against internal economics (CO, PR, AM), now extended to environmental (EV) and social (SC). The frame for a balanced KPI on a page.
Association for Supply Chain Management
Successor to APICS and steward of SCOR, the SCOR-DS dictionary, and the certification bodies of knowledge — the authoritative source for definitions when a metric on a notebook has to mean one specific thing.
SCOR × the canon
SCOR names the quantity; Parts I–IV decide how it is drawn and how the operator reads it. A supplier-OTIF gap becomes a dumbbell plot; forecast error against ±3σ becomes a control chart; a promise-date slip becomes a color on an otherwise gray panel.
How the reading becomes a notebook
Quiet by default, color on exception. The page is mostly neutral; the accent and the breach color are spent only on the one signal that needs the operator now.
The relationship picks the chart. A gap is a dumbbell, a trajectory is a fan, a driver mix is a Pareto — the form follows the question, never habit.
The subject stays fixed, the telemetry moves. Customers, suppliers, and SKUs are pinned to the decision; the operator changes what they see without rebuilding context.
These map directly to the A2go charting standard: one specification renders in both the analyst’s notebook and the product, themed to the brand token sheet and IBM Plex, so the picture in the brief and the chart in the console remain the same thing.
Instrumentation · The canon of charting & instrumentation — a reference for building instruments, not dashboards. Outbound links are to primary sources; where an edition or price is cited, confirm on the source. SCOR is ASCM's framework.
