Two questions, answered from how the work is actually performed.

Thirty minutes, occasionally up to an hour for larger or multi-company programs. To keep it to thirty, fill in the five-minute pre-assessment first: what the team does, which of its activities are directly tied to revenue and which are back office, how that work is paid for, and the systems it runs in. You leave the call knowing which assessment fits — or whether you need one at all — the fee, what could slow the install in your environment, and a realistic start date. A written scoping summary and draft proposal follow.

It is the entry point: $4,950, one team of up to 15 seats, two weeks of continuous desktop measurement, and a written report. It answers where the hours actually go, names the three largest recoverable patterns in hours per month, and says plainly whether a full assessment is worth doing — including when the answer is no. It skips the executive readout and the deeper analysis a Workforce or AI & Automation Assessment includes, which is why it costs a third as much. The whole fee is credited if you move up to a full assessment within 60 days of the report, so choosing it costs nothing but time.

Because self-logged fields rely on what people enter, not how the work was performed. Handle times, ticket timestamps, schedules, and self-reports can be entered late, rounded, or gamed, and they miss everything that happens between system events. In one team, six agents logged under three minutes per case and three logged over fifteen minutes for the same case mix — so the tracker's own occupancy report was meaningless. Dataken measures the work continuously at the desktop and uses your system data as a comparison, not as the source of truth.

At first, some may — that is the observer effect, and it is why interviews, workshops, time-and-motion studies, and a consultant watching over a shoulder give you a distorted picture. Dataken's measurement is different in two ways. It is passive: the OLi agent runs in the background on every in-scope desktop, so there is no one to perform for. And it runs for weeks, across the whole team, so any early change in behavior wears off and the data settles. We check this in every report: weekly totals typically land within a narrow band, with no first-week spike — in one month of telemetry across roughly 185 staff, all four weekly totals landed within roughly ±4% of the average. Data is anonymized at capture, and findings describe the work — hours, patterns, coverage — not a ranking of individuals.

The measurement period is three weeks for a Workforce Assessment and four weeks for an AI & Automation Assessment, the combined assessment, or a Portfolio Program. The clock starts once the OLi agent is installed on the in-scope desktops. What usually sets the start date is your security review: in regulated teams it can take longer than the measurement itself, so we start it in parallel with contracting, send the security package up front, and verify capture on a small pilot before the measurement period begins. The written report and executive readout follow the measurement period.

Yes, with one extra step. The OLi agent has to run inside the virtual session where the work is done, not on the thin client in front of it. We agree with your desktop engineering team on whether it goes into the VDI image or on the session host, and verify capture on a pilot seat before the measurement period starts. Mixed teams — some local, some virtual — simply get both install paths, with one of each in the pilot.

Yes, and it is often where the swivel-chair work hides — looking something up on a terminal screen and re-keying it into a newer system. Terminal screens carry less window detail than modern apps, so we include a terminal-emulator seat in the pilot and confirm what is captured before measurement begins. Terminal work is also frequently automatable, with a person approving each posting.

Yes. Activity is anonymized at capture, held inside a per-tenant boundary, and any model inference runs privately in zero-retention mode, so findings describe the work, not the patient, the card, or the customer. We prepare the data processing agreement — and a business associate agreement where PHI is involved — before your security review, not during it. Teams that handle regulated data also tend to get one finding they did not ask for: how much work is being pasted into public AI tools.

No — plan for it rather than around it. We provide an employee notice template and the anonymization model in week 0. Where a works council or union must be consulted, start that before contract signature: it can add weeks, and it is easier to agree on what is captured up front than to change it later.

Yes — that is the Portfolio Program: $55,000 for up to three portfolio companies of up to 75 seats each, $17,500 for each additional company, four weeks of measurement. Each company gets its own Workforce + AI & Automation report; you get a portfolio roll-up that converts measured, savable hours into an annual EBITDA range from each company’s loaded labor cost, and a ranked 100-day list per company. Each company’s approver signs off its own seats, from one shared security package, and measurement starts with the first approvals rather than waiting for all.

Yes — and we start with the question most vendors skip. If your clients pay for the hours or FTEs you provide, efficiency on billed work can reduce revenue, so the pre-assessment and scoping call separate billed work from the overhead around it. Savings aim first at the non-billable time — internal email, re-keying into your QA or billing trackers, admin — and at freeing capacity to take on new programs without hiring, not at shrinking what clients are billed for. Each client program gets its own measured evidence for that client’s business reviews. The desktops, data and often the VDI belong to each end client, so each program needs its client’s approval; we send one security package every approver can reuse and start with the first program approved. Many BPOs start with one or two programs of up to 75 seats at the fixed fee.

If you sign a first-year OLi deployment and implementation within 60 days of the readout, 100% of the assessment fee is credited against it. A $15,000 AI & Automation Assessment, for example, takes $15,000 off the first year. If you decide not to proceed, you keep the report and there is no further obligation.

No — it is measurement of the work, not surveillance of the person. Activity is anonymized at capture, held inside a per-tenant boundary, and analyzed with private inference. There is no keystroke logging and no full-screen recording. Findings are reported in aggregate — by team, hour, and work pattern — and where a report shows per-person load, such as occupancy, it is there to show how work is distributed across the team, not to rank individuals. The purpose is to decide staffing, schedules, and automation, and we recommend telling the team in scope what is being measured and why.

No free trials, and no — the guarantee does not apply to the assessment. Assessments are fixed-fee because they require a real deployment, a security review, and weeks of continuous desktop measurement to produce defensible numbers; the fee is credited toward deployment if you sign within 60 days of the readout. The guarantee — 10% more productive time in 30 days, measured against a baseline agreed at kickoff — belongs to the other way to start: skipping the assessment and deploying OLi directly. It is one path or the other.

You decide what to act on. If you proceed, Dataken implements the changes — OLi skills and automations at the desktop, help and training at the point of work, schedule changes, governance fixes — and then re-measures with the same instrument that produced the baseline, so the result is measured rather than estimated.

Process mining reconstructs a process from the event logs your systems already record. Task mining measures what happens on the desktop between those system events — the spreadsheet, the PDF, the three browser tabs, the copy-paste. Most cycle time lives in that gap, which is why process mining alone routinely under-reports the real cost of a process. Dataken's assessments are built on task mining at the desktop.

Lean programs find what observers can see, and people work differently while someone is watching. They systematically miss the private workarounds — the personal spreadsheet, the saved search, the reference document on the second monitor — because those are invisible during observation and unreported in interviews. Those workarounds are usually the bulk of what continuous desktop measurement surfaces, and the process often depends on them.

Dataken, Inc. is a Texas corporation headquartered in the Dallas–Fort Worth metroplex — our only office. Because the OLi agent is desktop software deployed to your endpoints, assessments are delivered remotely across the United States. On-site sessions in the DFW corridor can usually be arranged within the same week.