Discover Top Posts Tagged with #process governance

Process Control Mapping in Visio – Risk and Control Matrix Lens

Process control mapping in visio – risk and control matrix lens Most controls documentation has a credibility problem: The Risk and Control Matrix (RACM) lives in a spreadsheet. The process map lives in a diagram. They drift apart. Then the audit conversation becomes painful: • Which step does this control actually apply to? • Who owns it? • Is it preventive, detective, or corrective? • Did the process change after the matrix was approved? A practical fix is simple: Treat the process as data first. Use Visio as the renderer. With Visio Data Visualizer, a process can be stored as a dataset: • Step ID • Description • Next Step ID (connectors) • Function (swimlanes) • Phase (optional) Then create a controls lens from the same dataset. A clean starter controls lens: Function (swimlanes) = Risk category (Financial, Compliance, Cybersecurity, Quality, Safety) Phase (columns) = Control type (Preventive, Detective, Corrective) Now the diagram answers audit-grade questions at a glance: • Are controls only at the end (too late)? • Is the process over-controlled (approvals everywhere)? • Where is risk high with no control coverage? • Which teams own the controls that matter? • Where does rework happen because criteria are unclear? This is especially useful for SOX (Sarbanes-Oxley) style work and any environment where process and controls must stay aligned. Practical workflow: 1. Build or obtain the canonical dataset (Step IDs + Next Step IDs). 2. Add risk and control fields in the same workbook (risk category, control type, control owner, evidence). 3. Create a derived controls view dataset by mapping lanes and phases to risk and control classifications. 4. Render in Data Visualizer and review gaps with process owners and compliance. 5. Use Excel counts to quantify: number of controls, number of approvals, number of handoffs, number of loops. When everything is tied to Step IDs, governance gets easier: • A process change triggers a review of affected controls • Control owners are visible and auditable • Control rationalization stops being a subjective debate If converting an existing Visio diagram into the dataset format is the bottleneck, a dataset generator can create the import-ready TSV so controls mapping can start immediately. Lite can validate the workflow quickly. Standard is for when the dataset needs to scale beyond the pilot. A common pattern this lens exposes fast: Business-value work gets buried under review-by-default. Once it is visible, criteria and thresholds can replace blanket approvals. That is how cycle time drops without increasing risk. Comment “controls” if a starter template for risk categories and control types would help. #InternalControls #Compliance #Audit #ProcessMapping #Visio #GRC #RiskManagement process improvement, process mapping, operations, business analysis, workflow, visio, swimlane, automation, lean, standard work

#audit readiness #compliance #internal controls #process control mapping #process governance #Process Mapping #RACM #risk and control matrix #SOX controls #Visio Data Visualizer

One Process Model, Many Views (Pt. 3 of 3)

One process model, many views (pt. 3 of 3) The most expensive process mapping problem is not “drawing”. It’s redraw. Every time a leader asks for a new view: • “Show it by department.” • “Now show it by system.” • “Now show it by risk.” • “Now show it as a value stream map.” …teams create another diagram, and drift multiplies. The alternative is the same operating model used by serious architecture and process tools: Model = the dataset (the process as data). View = a diagram generated from that dataset. Lens = a controlled reclassification that produces a new view without changing the underlying process. This is “one process model, many views”. What has to stay stable: • Step IDs (unique, durable) • Next Step IDs (connections) • Step descriptions (can change, but IDs stay) Everything else is metadata that can be reclassified for different audiences. A practical approach that works with lightweight tooling: 1. Create the canonical dataset (the system of record) One row per step, plus connections. 2. Render the baseline view in Visio Data Visualizer Swimlanes and phases show the operational story. 3. Create lens datasets (copies or derived tables) The steps and arrows stay the same. Only Function and Phase (and optional lens columns) change. Examples of high-value lenses: • Value stream lens: Function = VA/BVA/NVA, Phase = Active/Waiting/Rework • Governance lens (RACI – Responsible, Accountable, Consulted, Informed): Function = Accountable role • Systems lens: Function = system of record used at each step • Automation lens: Function = automation potential (high/medium/low) • Risk lens: Function = risk category, Phase = control type (preventive/detective/corrective) Why this works in the real world: • Updates become row edits, not diagram surgery • Variants stop drifting because they share the same IDs and connections • Reviews get easier because the dataset can be versioned and diffed • Excel can quantify the map (handoffs, approvals, loops, counts by lens) • AI (artificial intelligence) tools become usable because they can read structured tables instead of screenshots Fast validation move: Convert 20 steps, import successfully, then change 1 lane assignment in the dataset and refresh. That round-trip is the moment the process stops being a picture and becomes a maintained model. If only one thing gets standardized, standardize Step IDs. That small discipline is what makes “many views” possible without chaos. Once the model exists, the work shifts from “draw and defend” to “measure and improve”. It also becomes easier to onboard new teams because the dataset is teachable. That speeds adoption. #ProcessMapping #Visio #DataVisualizer #BusinessAnalysis #Operations #ContinuousImprovement process mapping, raci, automation, risk and control, operations, business analysis, workflow, systems integration, decision rights

#Multi-view process mapping #Process analysis #process governance #Process lenses #Process Mapping #Process model #RACI #value stream mapping #Viewpoint based process modeling #Visio Data Visualizer

Turn a Process Diagram Into Process Data (Pt. 1 of 3)

Turn a process diagram into process data (pt. 1 of 3) Every process diagram already contains a dataset. It is just trapped inside the picture. That is why so many process maps fail: the map is “done”, but nobody can maintain it without reopening Visio and doing diagram surgery. If you can identify 3 things, you can turn a diagram into process data: 1. The steps (boxes) 2. The connections (arrows) 3. The owners and stages (lanes and phases) That is it. Once the process is a table, everything changes: updates become lightweight, analysis becomes spreadsheet-native, and Visio becomes a renderer instead of a drawing tool. Here is the minimum structure that works with Visio Data Visualizer: • Process Step ID (unique, stable) • Process Step Description (short, action-oriented) • Next Step ID (the Step ID(s) that follow) • Connector Label (optional) • Shape Type (Start, Process, Decision, End) • Phase (stage, optional) • Function (lane owner) A few rules matter more than people expect: • Step IDs must be stable. Do not renumber the process every edit. • Every Next Step ID must exist somewhere in the table. • Branching is represented by multiple Next Step IDs in 1 cell, comma-separated, no spaces. • No blank rows in the TSV file (tab-separated values) or the import can fail. • Standardize lane names early (Ops vs Operations vs Ops Team becomes 3 lanes). Why this matters commercially and operationally: If the process is data, the organization can finally answer questions like: • how many handoffs exist? • how many approvals exist? • where are the loops and rework paths? • what steps are waiting vs active? • what could be automated safely? And those answers stop being “opinions”. They become counts, pivots, and filters. A simple 20-step proof method: 1. Convert 20 steps from an existing diagram into rows. 2. Import into the cross-functional Data Visualizer template. 3. Fix formatting issues until it imports cleanly. 4. Change 1 row (move a step to a different lane) and re-import. If the diagram updates correctly, the process is now maintainable. This is Part 1 of a 3-part series: Part 1 – turn a diagram into data. Part 2 – apply the value stream lens (VA/BVA/NVA and Active/Waiting/Rework). Part 3 – generate many views from 1 model without redraw work. If only 1 thing happens this week: prove the round-trip. Import from data, make a change in the table, refresh the diagram. That is the moment a static map becomes a maintained model. Once that works, “1 process, many views” stops being a slogan. It becomes a repeatable workflow. Most teams never go back to redraw-based mapping after they see it. visio, swimlane, process mapping, operations, business analysis, workflow, data visualizer, automation, risk

#dataset format #Process analysis #Process data #process governance #Process Mapping #swimlane diagrams #TSV #Visio Data Visualizer

RACI in Visio – Keep Accountability Linked to the Process

Raci in visio – keep accountability linked to the process If RACI lives in a spreadsheet and the process lives in a Visio diagram, the 2 will drift. Then the workshop “answers” become shelfware: • People change roles. • Steps get added or removed. • Approvals get inserted. • The RACI table stays the same because updating it is nobody’s job. RACI is only valuable when it is attached to real steps. Quick definitions: RACI = Responsible, Accountable, Consulted, Informed. Common failure patterns: • Missing Accountable owners (no decision-maker) • Too many Consulted people (slow decisions) • Responsible and Accountable split across teams with no handoff clarity • A process map that looks clean, but hides an approval maze The practical solution is to make the process a dataset first, then generate the RACI view from the same source. With Visio Data Visualizer, the core dataset contains: Process Step ID | Description | Next Step ID | Shape Type | Function | Phase (optional) Then add RACI assignments in the same workbook (R, A, C, I) and create a derived “RACI view” dataset for visualization. Important detail: A single Data Visualizer shape can only sit in 1 swimlane. So the cleanest diagram is usually an Accountability view: Function (swimlanes) = Accountable role for each step That produces a diagram that answers the question leadership actually cares about: “Who owns each step?” A practical workflow: 1. Convert the process into a strict dataset (Step IDs + Next Step IDs). 2. Add RACI columns in Excel for each step. 3. Create a derived dataset where Function equals the Accountable owner. 4. Import into Data Visualizer. 5. Scan for missing A assignments and overloaded A lanes. 6. If needed, create a second derived view where Function equals Responsible. What to do with the findings: • If Accountable is missing – assign decision rights, or the process will stall. • If Consulted is everywhere – define criteria and reduce “review by default”. • If approvals are stacked – replace with thresholds and guardrails. • If 1 role owns everything – delegate, template, and push decisions down. This is also a clean setup for automation planning: automate stable, owned steps first, not committee steps. Now the RACI is no longer a detached workshop artifact. It is tied to the process model and can be updated with the same change-control loop as the diagram. If converting an existing Visio diagram into a strict dataset is the bottleneck, a dataset generator removes the friction by producing the import-ready TSV format so the RACI work can start immediately. Comment “RACI” if a simple starter template for RACI fields and lane rules would help. #RACI #ProcessMapping #Visio #DataVisualizer #Operations #BusinessAnalysis process improvement, process mapping, operations, business analysis, workflow, visio, swimlane, automation, lean, standard work

#Accountability #operating model #process governance #Process Improvement #Process Mapping #RACI #responsibility assignment #responsible accountable consulted informed #Visio Data Visualizer

Audit a Visio Process Map in Excel

Audit a visio process map in excel Most process maps are not auditable. If leadership asks 3 simple questions, a normal Visio swimlane diagram usually cannot answer them without a workshop: 1. How many handoffs are in this process? 2. How many approvals are we paying for? 3. Where does rework loop back and why? A picture is the wrong data structure for those questions. The practical fix is to convert the diagram into a dataset, then audit the dataset in Excel. Once the process is a table, the “audit” becomes counting and classifying, not arguing about shapes. The workflow is simple: 1. Convert the existing .vsdx diagram into a Data Visualizer-ready dataset (TSV or Excel). 2. Validate the dataset (unique Step IDs, valid Next Step IDs, no blank rows). 3. Open in Excel and add 5–8 audit columns. 4. Use pivot tables and a few lookup formulas to quantify the pattern. 5. Regenerate the diagram from data so the audit stays current. A fast audit checklist that works in real teams: • Handoffs – count edges where Function changes (lane-to-lane transitions). • Approvals – count decision steps and steps owned by approval tiers. • Rework – identify steps whose Next Step ID points backward. • Waiting – tag steps that represent queue, backlog, review, or “waiting for”. • Systems touchpoints – tag which tool is used at each step (ERP, CRM, email, spreadsheet, manual). • Risk and control – tag preventive vs detective vs corrective controls. • Automation readiness – tag high vs medium vs low automation potential. What to do with the numbers: • If handoffs are high, start with lane standardization and reduce ping-pong. • If approvals dominate, clarify decision rights and collapse unnecessary review layers. • If rework loops cluster, fix upstream criteria (inputs, definitions, templates). • If waiting is everywhere, the bottleneck is governance or capacity, not effort. Two common mistakes that keep audits weak: 1. Lane sprawl (Ops vs Operations vs Ops Team) – this hides handoffs and inflates lanes. 2. “Handle request” steps – vague text prevents classification and makes data analysis pointless. The win is not “Visio to Excel” as a shape dump. The win is “process as data” so Excel can do what it is good at: sorting, filtering, counting, and showing the story. A simple rule: If the process changes monthly, the diagram must be refreshable from data or it will become shelfware. Lite can validate the workflow on the first 20 steps. Standard removes the limit for full conversions and repeatable updates across a library of diagrams. If a process map cannot be audited, it cannot be managed. Auditable processes scale. #Visio #Excel #ProcessMapping #DataVisualizer #ContinuousImprovement #BusinessAnalysis #Operations process improvement, process mapping, operations, business analysis, workflow, visio, swimlane, automation, lean, standard work

#approval workflow #Continuous improvement #Excel process audit #handoff analysis #process governance #Process Mapping #swimlane diagrams #Visio Data Visualizer

Multi-view Process Lenses (RACI, Value Stream, Risk, Automation)

Multi-view process lenses (raci, value stream, risk, automation) Every stakeholder asks for a different “best version” of the same process map. Ops wants swimlanes by team. Leadership wants a value stream view (where time is wasted). Audit wants controls and evidence points. IT wants systems touchpoints. Automation teams want candidates and handoffs. Most teams respond the only way they can: redraw the process five different ways. That creates diagram sprawl and drift. Process lenses solve that problem. A lens is a controlled re-labeling of the same underlying process model to create a new decision-ready view without rewriting the process. The key requirement is simple: Model the process as a dataset first. Once the process is a table with: • stable step IDs • Next Step links (including branches and loops) • lane and stage fields …the diagram becomes output. Not the source of truth. Then a lens view becomes repeatable: 1. Copy the canonical dataset 2. Reclassify lanes and/or phases for the lens 3. Regenerate the diagram from the lens dataset 4. Summarize counts in Excel for fast insight High-value lens families that teams already recognize: • Value stream mapping (VA/BVA/NVA and Doing/Waiting/Rework) • RACI (Responsible/Accountable/Consulted/Informed) • Systems touchpoints (ERP, CRM, email, spreadsheet, manual) • Automation readiness (high/medium/low potential) • Risk and control mapping (preventive/detective/corrective) • Approval tier mapping (where governance slows throughput) Why this matters commercially: The lenses concept is what turns a one-time conversion into an ongoing operating model. One process model can produce multiple consistent views as questions change. The practical impact is real: • fewer “version” files • fewer debates about which diagram is current • faster executive readouts because the pattern is visible (handoffs, approvals, delay) • clearer ownership because lane assignments are controlled labels, not free text A practical start: Convert one real swimlane diagram into a dataset. Generate the baseline Data Visualizer diagram. Then create one lens view (value stream or RACI) to prove the method. When the dataset stays current, every lens stays current. A useful way to think about it: the dataset is the single source of truth, and each lens is a published view for a specific audience. That’s how the method stays credible and worth paying for. Once this is in place, the conversation changes from “can someone update the Visio” to “which view do we need for this decision.” That’s the difference between documentation and operating leverage. If a process has more than one stakeholder, it already needs more than one view. process improvement, process mapping, operations, business analysis, workflow, visio, swimlane, automation, lean, standard work

#automation readiness #Multi-view process mapping #one model many views #process governance #Process lenses #Process Mapping #RACI #risk and controls #systems touchpoints #value stream mapping #Visio Data Visualizer

Business Process Governance ensures process integrity by keeping employees aware of precisely how to manage decisions according to top-level goals and policies

#process governance