Teho
NORTHSTAR SERVICES GROUP · TEHO STUDY

Where skilled capacity is going.

A study of how a 37-person service and commercial team spends its time, where the biggest opportunities are, and how to redirect time into higher-value work.

Function studied
Service & Commercial Ops37 people · CSMs · Support · Service Managers
In scope, per year
£2.6Mblended £71k / person
Observation window
April 20264 working weeks
Reporting level
Team-level only82% evidence coverage
∗  DEMO CLIENT READOUT
Teho
Northstar · Service & Commercial Ops

Contents

What’s in this readout.

From the headline numbers to what comes next. Click any section to navigate there.

  1. 01Executive summaryThe headline number and the decision
  2. 02What was studiedOne function, four weeks, team-level only
  3. 03Coverage & confidenceWhat we’re sure about, and what we’re not
  4. 04Where the time goesThe £2.6M work catalogue, drilled to the task
  5. 05The Work ProfileThe same work, by area, type and cost
  6. 06How tools fragment workFour to five tools to handle one ticket
  7. 07Hotspots worth fixingSix problems, £481k, three to do first
  8. 08Grow the greenPutting freed time into high-value work
  9. 09Opportunity portfolioNine plays, tracked, with detail cards
  10. 10Decisions for leadershipFour choices — each with its proof
  11. 11Proving it landed — PulseHow we prove it moved · continue in Pulse
  12. 12Basis of calculationHow the numbers were worked out
  13. 13Privacy & what we didn’t look atTeam-level only, nothing about individuals
  14. 14What comes nextThe versioned document system
Teho · Do better workNorthstar · Worked example · Contents
Teho
Northstar · Service & Commercial Ops

01Executive summary

Recover £300k–£450k per year, across three common activities.

Northstar’s board approved an AI and transformation budget after renewals slipped. Before the Q3 budget lock, the COO asked a simple question.

The COO’s question

“Where is skilled service and commercial capacity being absorbed, and what should we simplify, redesign, automate or let AI help?”

£300–450k
Recoverable capacity - about 4–6 FTE.
£2.6M
Annual cost of the work we studied
48%
Of the time on low-value work (≈ £1.2M).
3
Hotspots worth fixing first - of 6 we found.
32%Judgement 20%Execution 21%Coordination 19%Overhead 8%Burden
Work mix of the reported 82% — full picture in section 0552% high-value · 48% low-value

What we found

  • Three everyday problems eat most of the lost time:
    P1 Building the same report by hand P2 Hunting for customer information P3 Reconciling numbers across systems
  • Two of those three aren’t AI shaped problems - they’re a report to automate and information to put in one place.
  • The skilled work; judgement, negotiation, coaching, difficult cases - should stay with people.

Why it’s like this

None of this is a people problem. Eighteen months ago Northstar bought a competitor and never merged the two customer systems, so people rebuild a customer’s history by hand before they can act. A client rule means a monthly report is still assembled by hand. Growth blurred who owns which decision.

The business changed faster than the work was redesigned. That’s fixable.

The decision

Pick the first two problems to fix, agree the ground rules, and choose what to track to prove it worked.

Teho · Do better workNorthstar · Worked example · 01
Teho
Northstar · Service & Commercial Ops

02What was studied

One function, four weeks, team-level only.

We looked at how the Service & Commercial Operations function actually works — never at how any one person works.

Scoped cohorts · 37 people

16Customer Success ManagersRenewals, expansion support, account coordination
14Support SpecialistsCustomer issue handling, triage, escalation support
6Service ManagersEscalations, quality, coaching, operational control

Over four working weeks in April 2026 we observed roughly 5,600 hours of work across these teams — always at team or workflow level, never individual.

The study boundary

  • Team-level evidence only
    Findings are repeated work patterns across cohorts — not individual activity scoring.
  • A 30-day observation window
    Plus about a week either side for set-up and readout prep.
  • Agreed evidence paths only
    Signals came from approved workplace tools and sources agreed with Northstar.
  • A pattern-graduation threshold
    A signal only became evidence once repeated across enough people, in scope, and past confidence checks.
The business question

One function, one question: where is skilled capacity going, and what should change first — so the budget backs the work that matters.

Teho · Do better workNorthstar · Worked example · 02
Teho
Northstar · Service & Commercial Ops

03Coverage & confidence

What we’re sure about, and what we’re not.

Of the work we observed, 82% cleared the evidence bar and is itemised in this report. The other 18% was emerging, suppressed or excluded — shown everywhere as a held-back allowance, never guessed or costed.

Confirmed
Seen often and widely enough to be confident. This is what the report is built on.
Use as evidence
Early signal
Showing up, but not yet confirmed. Flagged, not costed as fact.
Watch, don’t conclude
Too small to show
A group too small to show safely. Suppressed by design, never guessed.
Protected by design
Out of scope
Deliberately excluded — HR, personal, and anything agreed off-limits.
Never collected
What we don’t know yet
Three things this Study deliberately did not try to answer.
Long-term trendWhether the same patterns hold across seasonality, future quarters or different operating cycles.
Impact after changeWhether the decisions actually move the work mix, reduce friction or release capacity — that’s Pulse.
Wider scopeWhat excluded teams or unapproved evidence paths might reveal if Northstar widens the boundary.
Why this matters

A number you can defend beats a bigger number you can’t. Everything that follows sits inside this 82% — held to a standard a board can question.

Teho · Do better workNorthstar · Worked example · 03
Teho
Northstar · Service & Commercial Ops

04Where the time goes

The £2.6M, all the way down to the task.

Every pound of the studied work rolls up into six areas, and drills down through 18 activities to 64 costed tasks. Click any row to open it; the bar shows its work-type mix.

The six areas are the reported work — the 82% that cleared the evidence bar (£2.6M itemised). The grey “held back” row is the ≈18% that was emerging, suppressed or excluded: shown for honesty, never itemised. Renewals and Support are the biggest areas — and where most of the recoverable time lives.

Teho · Do better workNorthstar · Worked example · 04
Teho
Northstar · Service & Commercial Ops

05THE WORK PROFILE

The same work — by area, by type, by cost.

This is the £2.6M as a picture: each column is a work area (width = its cost), split into its activities. Click any column to drill into that area’s activities and tasks. Greens are high-value work to protect & grow; ambers and reds are low-value work to shrink.

The six areas are the reported work (the 82%); the grey column is the ≈18% held back — emerging, suppressed or excluded, never itemised. The red isn’t a column of its own — it’s mixed into every area. The visual twin of the table in section 04.

Teho · Do better workNorthstar · Worked example · 05
Teho
Northstar · Service & Commercial Ops

06How tools fragment work

Four to five tools to handle one ticket.

The information already exists — it’s just scattered. People hop between systems to pull it together, and the two un-merged customer systems are the visible cause. About £260k of the £481k friction traces straight back to it.

A typical path through one request

Emailrequest lands
Teamschase context
CRM #1look up account
CRM #2cross-check
Spreadsheetrebuild by hand

The same customer detail is looked up, cross-checked and re-entered across two CRMs that were never merged after the acquisition — connect them, and a chunk of this disappears.

Where the time concentrates

22% CRM systems 18% Spreadsheets 14% Messaging 46% Everything else

Dozens of tools in daily use · no AI tools in the mix yet.

What the fragmentation costs

Three of the six problems are pure consequences of scattered, duplicated systems — rebuilding, reconciling and re-entering the same information.

Hunting for information£104k Reconciling numbers£91k Double data entry£65k
Hunting for customer informationhistory rebuilt by hand from scattered systemsSimplify£104k
Reconciling numbers across systemsfigures that should match, but don’tAutomate£91k
Double data entry across two CRMsthe same record typed in twiceIntegrate£65k
System-fragmentation friction — of the £481k total£260k/ yr
The pattern underneath

Most of the lost time isn’t people working slowly — it’s the same information being rebuilt, re-entered and re-checked because the systems don’t talk to each other. Fix the plumbing once and the friction drains away.

Teho · Do better workNorthstar · Worked example · 06
Teho
Northstar · Service & Commercial Ops

07 THE HOTSPOTS WORTH FIXING

Six problems, £481k. Three to do first.

Each is a repeated, everyday problem we saw often enough to be sure about — in plain language, with what to do about it. 

Building the same report by hand
£130k5.0% of timeAutomate
A report clients require every month is put together by hand — copying numbers between systems and checking them. Same report, same steps, every cycle.
Hunting for customer information
£104k4.0% of timeSimplify
Before acting on a renewal, people pull a customer’s history together from different systems. The information exists — it’s just scattered, so it gets rebuilt by hand every time.
Reconciling numbers across systems
£91k3.5% of timeAutomate
Numbers that should match across systems don’t, so people check and correct them by hand before anyone can rely on them.
Double data entry across systems
£65k2.5% of timeIntegrate
The same details typed into two systems that were never connected after the merger.
Chasing decisions after meetings
£52k2.0% of timeRedesign
After meetings it’s often unclear who agreed to what, so people follow up and re-confirm — only because the decision wasn’t captured clearly the first time.
Answering repeat questions
£39k1.5% of timeLet AI help
The same known questions answered over and over — a good fit for self-serve answers and AI help.

Named problems total £481k. That’s the ceiling on the £300k–450k we’d expect to actually recover — itself a slice of the £1.2M low-value load. The numbers stay honest as you zoom in.

Teho · Do better workNorthstar · Worked example · 07
Teho
Northstar · Service & Commercial Ops

08Grow the green

The point isn’t to cut. It’s to grow the green.

Recovering time is only half the story. The prize is putting that time back into the work that wins and keeps customers — moving the team from 52% high-value work to 60%.

Today52% high-value · 48% low-value
32 20 21 19 8
After redesign — the target60% high-value · 40% low-value
36 24 17 16 7
Judgement · 32→36 Execution · 20→24 Coordination · 21→17 Process overhead · 19→16 Avoidable burden · 8→7
→ £208k of capacity from low-value to high-value work — doing more of what customers actually pay for.

Where the freed time goes

Three AI agents put recovered hours back into growth work — with a human leading every customer conversation. Revenue figures are illustrative, a scenario to pressure-test, not a forecast.

Renewal-brief agent
More save conversations
Freed time in£90–140k
Illustrative upside£100–200k
Support copilot
More complex cases handled
Freed time in£80–120k
Illustrative upside£70–130k
Service-review agent
Proactive account growth
Freed time in£60–100k
Illustrative upside£80–160k
£230–360k of freed capacity redirected into growth work→ £250–490k illustrative revenue
Teho · Do better workNorthstar · Worked example · 08
Teho
Northstar · Service & Commercial Ops

10Decisions for leadership

Four choices for the room.

Not an activity audit — a short set of decisions, each with the evidence behind it and the measure that will prove it landed.

Which two problems do we fix first?Wave 1
The evidence points to automating the monthly report and putting customer information in one place — the biggest, most repeatable wins, and neither needs AI.
ProofHand-built report hours per cycle · time rebuilding customer history per week
What are the ground rules?Before build
Don’t automate a broken report — drop the parts no one reads first. Keep a human check on the first cycle of anything automated. Don’t add more meetings as the fix for unclear decisions.
ProofHuman-review sign-off on the first automated cycle, before anything scales
Do we pilot one AI agent, and which?Wave 2
The renewal-brief agent is the strongest first test — it uses time freed in Wave 1 to create more save conversations. Pilot it once the information it needs lives in one place.
ProofSave conversations per at-risk renewal · renewal rate on the at-risk book
Do we commit to a quarterly Pulse?Ongoing
A one-off readout proves a moment; a Pulse proves a trend. Committing to the quarterly re-read is what turns these decisions into evidence that the work actually changed — covered next.
ProofWork mix 52% → 60% high-value · the three problems shrinking, quarter on quarter
Teho · Do better workNorthstar · Worked example · 10
Teho
Northstar · Service & Commercial Ops

11Proving it landed — Pulse

We saved a starting picture. Each quarter we check it moved.

The Study is the baseline. Pulse re-reads the same team the same way every quarter — proving the work shifted, not that a tool got adopted. The north star is more time on high-value work; the three priority problems are the early proof.

What we’ll watch — tracked against the April baseline

The three priority problems each get a plain measure tied to the work. Directional until a full quarter completes; anything from too small a group stays hidden.

Report built by hand
baseline 5.0%
Hunting for information
baseline 4.0%
Reconciling numbers
baseline 3.5%
The work mix moves toward high-value52% → 60%
Capacity-equivalent value realised, cumulative£300–450k

Team-level only — Pulse measures the work, never the worker. No individual monitoring is ever introduced.

□ Evidence of impact
Show whether the changes worked, and where value is emerging next.

Pulse turns this Study baseline into quarterly proof of work-mix movement, friction reduction, and capacity-equivalent value — without shifting into individual monitoring.

➚ Continue in Teho Pulse
Teho · Do better workNorthstar · Worked example · 11
Teho
Northstar · Service & Commercial Ops

12Basis of calculation

The figures are capacity-equivalent estimates, not savings claims.

No black box. Every headline figure traces to costed tasks and a stated assumption you can challenge — built on a loaded team-cost basis (£71k blended), never individual pay or performance data.

What the low and high ends assume

Low · £300k
Safe first moves
Only the highest-confidence fixes, with partial adoption. The number you can bank on.
Midpoint · realistic
First-wave portfolio
A typical first-wave mix — the two priority problems fixed, adopted at a normal pace.
High · £450k
All three, well adopted
All three priority problems redesigned and adopted well across the function.
MetricBasisGuardrail
£300–450kCapacity-equivalent value of the named, reportable friction patterns — confidence-adjusted and meant to be validated through decisions, delivery or Pulse.Not guaranteed savings, and not a plan to cut jobs.
≈ £481kSum of the six named problems — a realistic slice of the £1.2M low-value load, itself a slice of the £2.6M in scope.Not a complete ledger of every minute or cost.
≈ 4–6 peopleThe same hours translated to headcount-equivalent using the agreed £71k loaded team-cost basis.Not a headcount recommendation.
Growth revenueShown two ways — time redirected (grounded in the evidence) and revenue (a pressure-test scenario on Northstar’s own rates).Always marked illustrative — a scenario, not a forecast.
The chain that has to hold

Recoverable £300–450k  <  named friction £481k  <  low-value load £1.2M  <  in-scope £2.6M. Every number is a slice of the one above it.

Teho · Do better workNorthstar · Worked example · 12
Teho
Northstar · Service & Commercial Ops

13Privacy & what we didn’t look at

Team-level only. Nothing about individuals.

We only show patterns we saw often enough to be sure about, and only at team level. Nothing about individuals, and no group too small to be safe, is ever shown.

What we looked at
  • Approved signals about how work flows between tools and teams.
  • Rolled up to team and workflow level, with safe-size thresholds.
  • Checked by a reviewer against the agreed business question.
What we never looked at
  • No individual scores, rankings or timelines.
  • No keystrokes, no screenshots, no reading message content.
  • HR, payroll, legal, health, personal and union activity excluded.
No individual scoring No keystrokes / screenshots No message content HR / payroll / legal excluded Health / personal / union excluded
□ Why this should build trust
You can act on this readout without turning people into productivity data.

Teho is deliberately incomplete where the evidence would be unsafe, personal, sparse or outside the agreed question — and that restraint is what makes the findings usable. The excluded and held-back signals are shown as trust controls, not hidden as analysis gaps. The system would rather say “not enough evidence” than pretend every signal can become a leadership conclusion.

Teho · Do better workNorthstar · Worked example · 13
Teho
Northstar · Service & Commercial Ops

14What comes next · the document system

This readout sits in a versioned system of documents.

The immediate next step is to act on the decisions in §10 and commit to the quarterly Pulse in §11; a second function can be studied in parallel using the same method. Each artefact below answers a defined question about scope, method, evidence, governance, or what comes next — this readout is the leadership artefact, the rest are the system around it, versioned, owned and access-controlled.

Leadership artefacts
What should leaders read first?
Study Readout You’re reading it
This report: evidence, analysis, opportunities and decisions.
Executive Memo
Sponsor-ready narrative for board, ELT or steering updates.
Opportunity Portfolio Export
Decision candidates, routes, value ranges, confidence and proof metrics.
Scope & method
What was the Study designed to answer?
Study Charter
Pre-study question, boundary, cohorts, evidence paths and agreed exclusions.
Coverage & Confidence Statement
How reportable, emerging, excluded and limited evidence should be read.
Basis of Calculation
Loaded-cost basis, reportable-time method and capacity-equivalent guardrails.
Evidence assets
What data supports the findings?
Study Data Set
Versioned evidence tables used to produce the readout, under access control.
Work Taxonomy
Domain, activity, time-share, cost and the dominant work-mix hierarchy.
Evidence State Log
Pattern status, confidence, breadth, scope fit and suppression rationale.
Trust & governance
What can legal, procurement & InfoSec inspect?
Privacy & Non-Capture Appendix
Client-facing record of what Teho refuses to capture, analyse or report.
Study Privacy Posture
Purpose limitation, team-level reporting rules, retention and responsible-use.
DPA, Security & Data Residency
Data-processing terms, safeguards, hosting, subprocessors and access controls.
Trust Centre
Canonical public surface for Teho’s privacy, security and governance materials.
What comes next
How does evidence become a follow-on decision?
Leadership Decision Rail
The conversations Northstar should resolve before action starts (§10).
Pulse Baseline
Patterns, measures and cadence for proving whether selected work changed (§11).
Follow-up Study Brief
Questions needing more scope, more time, or a different team boundary.
Document Register
Current versions, owners, access level and request route for each artefact.
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