CASE STUDY

How Aarbakke is
Leapfrogging theIndustry and Taking
Control of Its DigitalFuturePartnering with Cognite, Aarbakke created an industrial data
foundation that:
Delivered 6% of annual revenue in recognized value
after 11 months
Reduced time to deliver new use cases from 6 months
to 1 month
Scaled to address 15 use cases (and counting) acrosstheir operations

COGNITE.COM

SECTION ONE

An Operational
Data Foundation
Built for Scale
Aarbakke’s journey began with an ambitious
two-person digital team with the objective ofbecoming a digital leader capable of delivering
many use cases across their value chain.
To achieve this objective, theyneeded an operational data
foundation with a reusable
data model to build solutions
across asset management,quality, sustainability, androbotics. Because the digitalteam was small, anotherimportant requirement

CASE STUDY: AARBAKKE

was to limit the effort
to maintain their data
foundation. Previous attempts
to create this foundation had
proven challenging. It took
an entire year just to connect
all the equipment on theshop floor, with minimal value
delivered to operations.

2COGNITE.COM

Aarbakke chose to partner withCognite for the second attempt
to develop an operational
data foundation that met thecompany’s needs.

Cognite Data Fusion, an Industrial
DataOps SaaS offering, was able
to integrate and contextualize
all of Aarbakke’s machine data
in weeks instead of months. In
addition, Cognite Data Fusion
integrated data from Aarbakke’s
MES, ERP, quality system, andtooling database. The end result
was a rich data foundation with areusable data model.
Combining this data modelwith Cognite’s open, API-first
approach made data meaningful
and accessible for Aarbakke’s
digital team to deliver usecases. To reduce the effort tomaintain solutions, Cognite
Data Fusion also provided thedata governance and quality
monitoring required to minimize
the data management burden on
Aarbakke’s digital team.

CASE STUDY: AARBAKKE

3COGNITE.COM

COLLECT, INTEGRATE, ACCESSThe efficiency gains in creating Aarbakke’s industrial data
foundation can be seen at each step of the process:Without Cognite
Data Fusion

With Cognite
Data Fusion

Set up infrastructure:

Set up infrastructure:

Previous tools required
server infrastructure tohost the databases—didnot scale well with newmachines and routinely
overloaded CPUs
resulting in downtime

Zero effort needed fromcustomer in order to host
raw and clean data

1 solution architect (SA)for 1 week + perpetual
solution architectureneeded for at least 1 day
per month

CASE STUDY: AARBAKKE

Everything provided asSaaS

Minor cost savingsin 1st setup, but
major cost savingsin scalability

4

COLLECT, INTEGRATE, ACCESSCOGNITE.COM

Without Cognite
Data Fusion

With Cognite
Data Fusion

Access:Access:Previous systems did
not support Azure AD
integration, so continuous
updating of users/loginsrequired
Perpetual IT admin needfor 1 day per month
Possible data breaches

Ingest:Out-of-the-box; but
does not support theentirety of data sent frommachines
Only supported a verysmall subset of additional
data sources
1 Solution Architect for
1 week to deliver

Out-of-the-box integration
with Azure AD
Granular data access tounderlying data supports
better collaboration/data
sharing with customers
and suppliers
1 Solution Architect for
1 day

Ingest:Custom extractor utilizing
Python toolkits and open
APIs (significantly moredata than previous tool 10X
increase in available datafrom 15 time series permachine to 150 time series
per machine
Fully scalable andautomatically onboards
new machines
Out-of-the-box extractors
for database setup in days
Time: 2 Solution Architects
for 2 weeks

CASE STUDY: AARBAKKE5CONTEXTUALIZE AND UNDERSTAND

COGNITE.COM

Without Cognite
Data Fusion

With Cognite
Data Fusion

Contextualize:

Contextualize:

Significant manual
effort to set up static
dashboards for eachmachine
Information models exist
per solution
1 subject matter expert(SME) for 4–5 months

Visualize:
Custom solution fromsoftware vendor; lowcode tool, but outdatedvery quickly
Did not allow for best-inbreed visualization
Resources included inContextualize phase(above)

Flexibly-adopted protocol
standards automaticallyfor all machines
See Ingest (above)
First machine = 2 weeks
Next 50 machines = 2hours

Visualize:
Connector to Qlik Sense(BI tool) developed with
open Cognite API
1 Solution Architect for
2 weeks Out-of-the-box
use of Grafana
Use of open-source
tools like Plotly Dashwith Python SDK for fully
custom front ends
Choose best applicationfor each use case

CASE STUDY: AARBAKKE6DEVELOP AND DEPLOYCOGNITE.COM

Without Cognite
Data Fusion

With Cognite
Data Fusion

Evaluate /data
exploration:

Evaluate /data
exploration:

There was no goodplace to store thecontextualization;
all of it was done inconfigurations specific to
the use case (similar to alarge Excel spreadsheetwith mappings)
Average new solution
would require 1 dataengineer plus 1 data
scientist or SME 4 weeks
to find and prepare data

CASE STUDY: AARBAKKE

Supporting both data
scientists and the SME tofind the required data for
the use case using fusion
UI and the Python SDK
Average new solution
would require 1 Data
scientist or SME 1 week
to find and prepare data7

COGNITE.COM

Without Cognite
Data Fusion

With Cognite
Data Fusion

Deploy:Deploy:DEVELOP AND DEPLOY

Running Docker orPython jobs on dedicatedservers
Would always require
data engineers for
deployment
Depending on server
load, would occasionallyrequire increasing server
capacity (not a significant
cost, but efforts toacquire more capacity
slows project delivery)

CASE STUDY: AARBAKKE

Cognite functions
No need for solutionarchitects to be involvedin cloud hosting
SME is able to deploy
independently
Time saved: 2 dataengineers (IT specialist)
for 1 week8

COGNITE.COM

Without Cognite
Data Fusion

With Cognite
Data Fusion

Monitoring thesolution:

Monitoring thesolution:

MONITOR AND GOVERN

Only alerted reactively byusers if the solution went
down
Limited ability totroubleshoot orinvestigate

Data governance:
Laborious to selectively
share data with partners
or other externals(impossible for somedata)

Active monitoring on all
deployed solutions“Data Lineage” makes
troubleshooting easier
Estimated reduced
time to RCA (root causeanalysis) for a dataengineer is 4 hours

Data governance:
All Cognite data setsconnected/governed inAzure AD—automatic
permissioning forexternals/partners
Time saved: 1 IT
consultant for 2 daysfor every batch of data
shared externally

CASE STUDY: AARBAKKE

9COGNITE.COM

Without Cognite
Data Fusion

With Cognite
Data Fusion

Data lineage:

Data lineage:

MONITOR AND GOVERNNo or very limited
documentation of datalineage

CASE STUDY: AARBAKKE

Easy to store and manage
data lineage through datasets, transformations etc.
Aarbakke’s IT consultant
is now building inCognite Data Fusion(e.g. Transformations) tomaintain transparency
and make it easier tomodify in future

10COGNITE.COMSECTION TWO

Applicationand Solution
Development
Delivering value with an operational data
foundation is determined by the speed, scale, andimpact of the use cases created.
Aarbakke and Cognite
began delivering use cases
within the first 8–12 weeks of
their partnership, enabling
Aarbakke to increase theirmachine utilization by 10%,
reduce machine service costs
by 25%, and optimize their
tooling to reduce excess
inventory by 60%.

CASE STUDY: AARBAKKE

Aarbakke and Cognite
began delivering usecases within the first

8-12weeks

11COGNITE.COM

60%

reduction inexcess inventory

25%

reduction in machineservice costs

10%

increase in machineutilization

CASE STUDY: AARBAKKE

12COGNITE.COM

More importantly, because
the data model is built tobe reused across use cases,
the time and effort to deliver
these continually decreased.
Ultimately, Aarbakke’s team saw
a fivefold increase in solutionsdelivered: they delivered 15
over the next 18 months,
compared with only three every
18 months previously.
Additional use cases included anenergy monitoring solution toreduce energy consumption andreal-time quality reporting that

reduced the number of quality
incidents by 10%. In just undera year, the two-person digitalteam at Aarbakke was able todeliver 6% of annual revenue inrecognized value.
Aarbakke’s digital team has
continued to build out theirindustrial data foundation and iscurrently developing a solution
to cut CO2 emissions, with theambition of becoming one of
the world’s greenest suppliers in
the energy sector.

Aarbakke’s team saw a fivefold increase in solutions delivered: they achieved

Without Cognite DataFusion: 3 use cases in18 months

With Cognite Data
Fusion: 15 use casesin 18 months

CASE STUDY: AARBAKKE

13COGNITE.COM

SECTION THREE

Cognite’s Role
Beyond Technology
Owning, developing, and maintaining digital solutions is
an important initiative for Aarbakke.
Growing their digital maturity todeliver solutions in weeks insteadof months required the righttechnology and the right partner.
While those steps shortened
Aarbakke’s initial time to value,
the path to becoming digitally
mature requires an environmentthat fosters continuous learning.
This is why Cognite provides
education, training, and support
to enable Aarbakke to expand theusers of the data foundation to allof its data consumers.

CASE STUDY: AARBAKKE

The democratization of data,
combined with the right support,
has continued the accelerationof use cases and allows subject
matter experts to answer
questions in minutes instead ofweeks.
With access to educationalcourses through Cognite
Academy, as well as to theCognite Data Fusion user
community through Cognite Hub,
Aarbakke’s digital team is truly
empowered to take control oftheir digital future.

14COGNITE.COM