Blog post schedule: October – December 2026

Blog post schedule: October – December 2026

One post per week, published on Mondays (matching the Jul 20 / Jul 27 / Aug 3 / Sep 7 cadence). Every topic is an analytics method an SME can apply to data it already collects, following the blog’s running theme: replace gut feel with a number.

What has already been covered (do not repeat)

Date Post Method
2026-07-21 Can AI really help business decisions Strategic / tactical / operational framing
2026-07-22 Lead conversion analytics Funnel conversion, CAC, CLV
2026-07-27 Inventory control for SMEs ABC classes, EOQ, reorder points, safety stock
2026-08-03 Market basket analysis Association rules (support, confidence, lift)
2026-08-07 Portfolio optimization Markowitz mean-variance
2026-08-08 Which capital projects to fund Capital budgeting: NPV, IRR, payback
2026-08-09 Customer profiling and segmentation RFM, clustering
2026-08-27 Working capital tied up in inventory Inventory turns, DIO, cost of capital by unit
2026-08-29 Keeping quality under control SPC control charts, Cp/Cpk capability
2026-09-07 Orders on time and in full OTIF, 3PL / warehouse KPIs, root-cause Pareto

Gaps worth filling: forecasting (nothing yet), pricing, staffing, experimentation, sales pipeline, churn, the inbound supply side, product profitability, receivables, cash flow, expense controls, and planning / KPI design for the new year.

Conventions (from the existing posts)

  • Filename is a question slug: YYYY-MM-DD-how-can-....md. Recent posts have no YAML front matter and no body H1; Jekyll derives the title from the slug.
  • Opening: a concrete “gut feel” scenario, then a paragraph linking 2–3 earlier posts with “replace gut feel with a number”, then bold the method name.
  • Section skeleton: What X actually gives you → A practical example, using this repo’s own results → 2–3 finding sections → The business impact, in real numbers → What to actually do with this, this week → Try it yourself (Downloading the code / Running the demo) → Understanding the results → The limits worth keeping in mind.
  • Each post is backed by a public demo repo: synthetic data generator → validate → analyze, run with --seed 42, outputs an Excel workbook. Screenshots are Excel tabs captured via COM, trimmed, max 700 px wide, saved as assets/images/<date>-<name>.png.

Schedule

Status legend: [ ] not started · [d] demo repo done · [w] draft written · [x] published

October — getting ready for peak season

  • [w] 2026-10-05 — How can a small business forecast next month’s demand?
    • Why SMEs care: Q4 ordering decisions are being made now; every inventory post so far assumed demand was known. This closes that loop.
    • Method: seasonal naive baseline, moving average, Holt-Winters (ETS); MAE / MAPE on a holdout; forecast bias; how forecast error feeds safety stock.
    • Demo: 3 years of weekly sales for ~30 SKUs with trend + seasonality + promo spikes; workbook with per-SKU forecast vs actual, accuracy league table, “which SKUs are forecastable”.
    • Links back to: inventory control (2026-07-27), working capital (2026-08-27).
  • 2026-10-12 — How should a small company set its prices?
    • Why SMEs care: most SMEs price at cost-plus or copy a competitor; holiday promotions are about to be planned with no idea of elasticity.
    • Method: price elasticity from historical price/volume, log-log regression, contribution margin impact, markdown depth vs. lift, break-even lift for a discount.
    • Demo: transactions with several historical price points per product; workbook with elasticity per product, “safe to raise” vs “price-sensitive” lists, promo scenario table.
    • Links back to: market basket (2026-08-03), lead conversion (2026-07-22).
  • 2026-10-19 — How many staff do you actually need on a Saturday?
    • Why SMEs care: shops, cafés, call desks and clinics over- or under-staff by habit; wages are usually the biggest controllable cost.
    • Method: arrival rate by hour/day, Erlang C / simple queueing, service-level targets (e.g. 80 % served within 5 min), staffing curve, cost of idle time vs. cost of lost customers.
    • Demo: POS / ticket timestamps for 6 months; workbook with hourly heatmap of arrivals, required-staff grid per hour, current roster vs. required, cost comparison.
    • Links back to: OTIF (2026-09-07, same “customer’s side of the fence” framing).
  • 2026-10-26 — Did that promotion actually work? A/B testing for small businesses
    • Why SMEs care: Black Friday emails, discount codes and layout changes get judged on “sales went up”; nobody checks whether the difference is noise.
    • Method: two-proportion z-test / chi-square for conversion, t-test for basket value, minimum sample size, confidence intervals, common pitfalls (peeking, seasonality, novelty).
    • Demo: email campaign split with control/treatment groups; workbook with results, p-values, CIs, sample-size calculator tab, “how long to run the next test”.
    • Links back to: lead conversion (2026-07-22), pricing (2026-10-12).

November — customers, suppliers and margins

  • 2026-11-02 — How much of your sales pipeline will actually close this quarter?
    • Why SMEs care: B2B SMEs plan hiring and cash on a pipeline total that is mostly wishful thinking; year-end quota pressure makes it worse.
    • Method: stage-weighted pipeline, historical win rates by stage / deal size / age, logistic regression for win probability, pipeline coverage ratio, slippage analysis.
    • Demo: CRM export of ~1,500 opportunities over 2 years; workbook with win-rate matrix, weighted forecast vs. naive total vs. actual, “stale deals” list.
    • Links back to: lead conversion (2026-07-22), demand forecasting (2026-10-05).
  • 2026-11-09 — Which customers are about to leave, and can you stop them?
    • Why SMEs care: subscription, service-contract and repeat-purchase businesses lose customers silently; win-back is far cheaper before the customer has gone.
    • Method: defining churn for non-contract businesses, features from RFM and behaviour, logistic regression / decision tree, lift and gains chart, expected value of an intervention.
    • Demo: customer base with monthly activity; workbook with churn-risk ranked list, model accuracy, “top 100 to call this week” with expected revenue saved.
    • Links back to: segmentation (2026-08-09), lead conversion (2026-07-22).
  • 2026-11-16 — Which suppliers are quietly costing you money?
    • Why SMEs care: OTIF covered the outbound side; the inbound side (late, short or defective deliveries) drives the safety stock and stockouts from the inventory posts.
    • Method: supplier scorecard: on-time %, fill rate, lead-time mean and variability, defect PPM, price variance; weighted score; lead-time variability → safety stock cost.
    • Demo: purchase orders and receipts for ~25 suppliers; workbook with scorecard, lead-time distribution per supplier, “cost of unreliability” per supplier.
    • Links back to: OTIF (2026-09-07), inventory control (2026-07-27), SPC (2026-08-29).
  • 2026-11-23 — Which of your products actually make money?
    • Why SMEs care: revenue rankings hide the fact that the best seller may be the worst earner once handling, returns and shelf space are counted.
    • Method: contribution margin per product, simple activity-based cost allocation, break-even volume, product-mix optimization with a linear program under a capacity constraint.
    • Demo: product master with costs, sales and capacity usage; workbook with margin waterfall, revenue-vs-margin scatter, optimal mix vs. current mix and the profit difference.
    • Links back to: pricing (2026-10-12), capital budgeting (2026-08-08).
  • 2026-11-30 — Why is the cash from your sales arriving so late?
    • Why SMEs care: receivables are the other half of working capital; year-end is when slow payers hurt most.
    • Method: DSO, ageing buckets, collection effectiveness index, customer payment-behaviour scoring, prioritised dunning list, cost of financing late payments.
    • Demo: invoice and payment ledger for 2 years; workbook with ageing table, DSO trend, customer payment profiles, “call these first” list with cash impact.
    • Links back to: working capital in inventory (2026-08-27), churn (2026-11-09).

December — cash, controls and planning for 2027

  • 2026-12-07 — Will you run out of cash in January? A 13-week cash flow forecast
    • Why SMEs care: December sales, January tax and rent, and slow receivables collide; a rolling 13-week view is the single most useful finance tool an SME can build.
    • Method: direct-method weekly cash forecast, receipts from receivables ageing (2026-11-30), payments from purchase commitments, scenario ranges (base / slow-collections / lost customer).
    • Demo: combines the receivables, payables and payroll data; workbook with weekly cash curve, minimum cash point, scenario fan, “actions that move the curve”.
    • Links back to: receivables (2026-11-30), demand forecast (2026-10-05), inventory working capital (2026-08-27).
  • 2026-12-14 — Are there expenses in your books that shouldn’t be there?
    • Why SMEs care: year-end close; duplicate invoices, split payments to dodge approval limits and out-of-pattern spend are common and usually found by accident.
    • Method: duplicate detection (fuzzy match on amount / vendor / date), Benford’s law on amounts, threshold clustering just under approval limits, z-score / IQR outliers by vendor.
    • Demo: 20,000 expense lines with a handful of planted anomalies; workbook with flagged lines by test, Benford chart, vendor outlier list, review checklist.
    • Links back to: SPC (2026-08-29, same “is this normal variation?” idea).
  • 2026-12-21 — Why did you miss budget, and what should next year’s look like?
    • Why SMEs care: the annual budget review usually stops at “we were 8 % under”; variance analysis says why, and a rolling forecast stops the budget going stale by March.
    • Method: price / volume / mix variance decomposition, flexible budget, variance bridge (waterfall), driver-based rolling forecast.
    • Demo: budget vs. actual by product and month for one year; workbook with variance bridge, volume-vs-price-vs-mix table by product line, 2027 driver-based forecast template.
    • Links back to: product profitability (2026-11-23), demand forecast (2026-10-05).
  • 2026-12-28 — What should be on your one-page dashboard for 2027?
    • Why SMEs care: year-end reflection post. Ties the whole year of posts together: which 10–12 numbers an SME owner should look at weekly, and how to set targets for them.
    • Method: leading vs. lagging indicators, KPI trees (cash ← receivables, margin, stock), target setting from the historical distribution, control-chart thinking for KPIs (when a KPI move is real), dashboard layout principles.
    • Demo: a single workbook / Power BI-style one-pager fed by the earlier demo datasets; one tile per post of the year, with the “what to do when it moves” note on each.
    • Links back to: every post since July (this is the year-in-review).

Working notes

  • Publish Mondays; if a post slips, keep the slot order (each post links back to the previous ones and the December posts build on November’s data).
  • Reuse the same synthetic company across the November–December finance posts (receivables → cash flow → variance → dashboard) so the numbers reconcile between posts.
  • Keep the Excel-workbook-plus-Python-scripts demo format; SME readers are Excel-first.

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