Solution · Intelligent Operations

Most organisations are not short of reports

They lack reports that answer the question being asked in the meeting. This solution builds analytics around the decisions that they exist to support, commencing with the decision rather than the data warehouse.

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Overview

Reporting built backwards from the decision

A reporting estate is only as useful as the decisions it changes.

X-Shift designs the analytics layer around the decisions that an organisation makes repeatedly (where to allocate capacity, which service to prioritise, whether an intervention was effective) and then specifies the measures, definitions and data quality on which those decisions depend. Metrics are defined once and owned by a named individual, so that the same term carries the same meaning in two departments. Operational views are built for the people managing the day and summary views for the people deciding the quarter, from the same governed definitions. Where the underlying data cannot yet support a decision, this is stated as a finding rather than obscured within a visualisation.

Key features

Key features

01

Data analytics

Analysis is performed across operational, service and experience data to answer defined business questions.

Data & Digital Intelligence Illustrative
FEATURE Data analytics By segment Business intelligence 88% Dashboards 71% Operational intelligence 64% Voice 43% Digital 29% Period rolling 12 weeks Figures illustrative

KPI monitoring

Defined indicators are tracked against target, with variance visible and attributable.

Decision support

Analysis structured around recurring decisions rather than around available data.

Reporting

Scheduled and on-demand reporting for governance forums, with a consistent basis between periods.

Trend analysis

Movement over time is separated from noise, so that genuine change can be distinguished from variation.

The challenge

Reporting volume is not the constraint

The typical enterprise produces far more reporting than it uses.

Dashboards proliferate because each request for information produces a new one, built by a different team from a different source. The result is several figures for the same measure, disagreement about which is correct, and executives who request analysis because they do not trust the dashboard. The problem is rarely tooling; rather, nothing was designed around the decision that the reporting was intended to inform.

Several versions of the same metric, none of which has been agreed

Dashboards built per request rather than per decision

Operational data and experience data reported separately

Analysis requested manually because the reporting is not trusted

No defined owner for a metric's definition

Reporting that describes what occurred without indicating the action required

Our approach

Commence with the decision, not the data

The order matters more than the tooling.

X-Shift commences with the decisions that you make repeatedly: where to allocate capacity, which service to prioritise and whether a change was effective. The approach then works backwards: what must be measured, how it must be defined, and which data must be trustworthy. Reporting built this way is smaller, better used and considerably easier to govern. Where the underlying data cannot yet support the decision, this is a finding that is valuable to obtain early.

Outcomes

What changes for the organisation

What this changes

Fewer reports, greater agreement, and less time spent debating whose figure is correct.

01

One agreed definition per metric, with a named owner

02

Reporting designed around recurring decisions

03

Operational and experience data read together rather than separately

04

Trends distinguishable from normal variation

05

Less manual analysis commissioned to verify the dashboards

06

Governance forums working from a consistent basis between periods

Use cases

Meetings that ask for analysis every month

Each is a recurring decision that the existing reporting describes but does not support.

01

Two entities, two definitions with X.Orbit

Situation

Two entities under the same ministry report beneficiary service volumes using different definitions of a completed request, and the consolidated figure satisfies neither of them.

What happens
  1. Identify the customer
  2. Create and classify the case
  3. Apply SLA and owner
  4. Resolve and close
Outcome

One definition is agreed and owned by a named individual, and both entities report against it under the same rule.

Commonly applied in Government and across other sectors

02

Monthly capacity decided on instinct with X.Orbit

Situation

Leadership decides every month where to allocate contact centre and branch capacity, and the dashboards show last month's volumes without indicating where the next month's will fall.

What happens
  1. Identify the customer
  2. Create and classify the case
  3. Apply SLA and owner
  4. Resolve and close
Outcome

Reporting is rebuilt around the capacity decision, so that the meeting is presented with the measures that the decision requires.

Commonly applied in Banking and across other sectors

03

Operational and experience data reported separately with X.Orbit

Situation

Waiting times are reported by operations and patient satisfaction by the experience team, and no report demonstrates whether the clinics with long waits are those with dissatisfied patients.

What happens
  1. Identify the customer
  2. Create and classify the case
  3. Apply SLA and owner
  4. Resolve and close
Outcome

The two are read together at clinic level, so a correlation can be tested rather than assumed in a meeting.

Commonly applied in Healthcare and across other sectors

More ways to apply it

A dashboard per request with X.Orbit

The estate is reduced to the decisions that it supports, and the remaining measures have one definition and one owner.

Retail

Intervention results claimed without a baseline with X.Orbit

The measure and the comparison period are established before the intervention, so that the result can be examined rather than disputed.

Utilities

Trend or noise, determined by visual inspection with X.Orbit

Normal variation is shown explicitly, so that the review acts on genuine movement rather than on the shape of a line.

Telecommunications
Explore by industry

These are illustrative applications rather than client engagements. The decision to rebuild first is typically the one that continues to generate requests for manual analysis.

Common questions

What buyers ask before committing

Next

Where to go next

Rebuild one decision's reporting

Select a decision that your leadership makes every month, and review the measures, definitions and data quality that it requires, alongside what the current reporting supplies instead.

Applicable where a recurring meeting continues to request analysis that the dashboards cannot provide.

Request a decision workshop

Establish the definitions first

Data Governance & Management establishes metric ownership, definitions and quality standards, which prevents the same disagreement from reappearing in the next set of dashboards.

Applicable where two departments report different figures for the same measure.

Data Governance & Management

Where the underlying problem is ungoverned definitions rather than reporting design, X-Shift will advise accordingly and propose the governance work first.

Where this sits

Related

Designed byData Governance & ManagementThe definitions and ownership underneath it.
Designed byEnterprise ArchitectureData architecture across the estate.
Designed byReporting & Performance ManagementReporting operated as a managed service.
Deployed asQuality Management & Interaction AnalyticsInteraction data feeding the wider picture.

Also relevantProcess Orchestration & AutomationDigital Governance & Operating Model

Is this the capability you require?

Describe what is not working today, and we will advise whether this is the right answer, a smaller piece of work, or an entirely different problem.

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