mid term –participants survey review hartree centre...statements of work-relating to each of the...

THE HARTREE CENTRE’S INNOVATION RETURN ON RESEARCH (IROR) PROGRAMME: MID TERM – PARTICIPANTS SURVEY REVIEW

Compiled by: Cambium LLP, Eco-Innovation Centre, City Road, Peterborough www.cambiumllp.com

© Cambium LLP – all rights reserved

ACKNOWLEDGEMENTS 3GLOSSARY 4EXECUTIVE SUMMARY 5

Survey scope 5Findings 6Recommendations 7

INTRODUCTION 8The Hartree Centre and the IROR Programme 8

SURVEY APPROACH 9SUMMARY OF SURVEY FINDINGS 10ANALYSIS OF SURVEY RESPONSES 131. Engagement of IROR Participants in the review process 13

2. Time to market / time to implementation 143. Reduced skills dependency 154. Knowledge capture and retention 175. Reduced costs 19

RECOMMENDATIONS 211. Business value monitoring 212. Increase executive sponsorship within IROR projects 213. Assessing the value of IROR digital assets 214. Best practices in the use of data-intensive technologies 22

APPENDICES 23APPENDIX 1 – Statement of Work (SOW) Models 23APPENDIX 2 – THE IROR Industrial Engagement Process – InCEPTTM 24

CONTENTS

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© Cambium LLP – all rights reserved 3

About the Hartree Centre:The Hartree Centre is transforming UK industry through

high performance computing, big data and cognitive

technologies.

It is part of the Science and Technology Facilities Council

(STFC), which is under UK Research and Innovation (UKRI).

About CambiumCambium specialise in accelerating adoption of data –

enabled innovation that tackles high priority business-led

challenges. For over a decade, they have enabled faster

innovation by developing highly effective partnerships

between public and private sector organisations using

novel collaboration processes, such as InCEPTTM.

ACKNOWLEDGEMENTS

The Hartree Centre and Cambium would like to thank all those involved in the IROR

programme, especially those that took part in the survey.


GLOSSARY

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AI Artificial intelligence

CFD Computational fluid dynamics

Digital asset Software components that have been used and may be reused to address a business challenge / need.

HC Hartree Centre

HPC High Performance Computing meaning the practice of practice of aggregating computing power to deliver very high performance and solve large complex problems in science,engineering, or business

InCEPTTM Industrial Collaborative Engagement for Proof of Technology. A collaborative innovation process used by Hartree Centre to accelerate translation of research to satisfy real businesschallenges and create digital assets

IROR Innovation Return on Research – a challenge-led industrial engagement programme that aims to translate research in data centric technologies into beneficial and measurable impact

JDA Joint development agreement

ML Machine learning

MNC Multinational corporation

PaaS Platform as a Service

Participants Commercial organisations that have participated in the IROR programme

SCD Scientific Computing Department at STFC

SME Small or medium sized enterprises – The usual definition of small and medium sized enterprises is any business with fewer than 250 employees

SOW Statements of Work-relating to each of the domains identified for the IROR programme. That is Chemistry & Materials, Science, Engineering & Manufacturing,Life Sciences and Enabling Technology

STEM Science, technology, engineering and mathematics – usually referring to skills or expertise

STFC Science and Technology Facilities Council, part of UK Research and Innovation (UKRI)

TRL Technology Readiness Level – method of estimating technology maturity across different types of technology

UQ Uncertainty Quantification, the science of quantitative characterisation and reduction of uncertainties


Innovation Return on Research (IROR) is a challenge-led industrial engagement programme for thetranslation of research in next generation data-intensive technologies into digital assets and UKeconomic impact. The type of business challengesbeing addressed through IROR are complex andinvolve higher risks than any individual companywould be able to undertake in isolation.

This review is based on a detailed survey of nineindustrial organisations (Participants)1 , from apotential pool of 20. The Participants also representa diverse range of business sectors, organisationsize and business models. Close engagement withthese Participants during the first six to 18 monthsof the programme has indicated that the researchoutcomes in their projects are closely aligned totheir business challenges.

Survey scopeThe report, produced by Cambium, covers the workcarried out in three industry application domains(referred to internally and within this document asStatements of Work or SOWs):

• Science, Engineering & Manufacturing (SEM)• Chemistry & Materials • Life Sciences

The programme of work also includes developmentof enabling technology which underpins all threeareas but is not included as part of this review.

This report forms part of a review by the HartreeCentre as part of the five-year IROR programme.Consequently, each project area is still in progress,therefore the analysis describes the benefits acquiredfrom the Participants’ involvement to date. For themost part, this analysis refers to the Participant’sviews of the expected future benefits of theresearch rather than to impacts experienced so far.

To date, IROR has enabled a clearer, better informedview of these potential benefits. In many cases thescope of individual research projects has introducedkey milestones to assess and validate these outcomes.

However, this review should not be seen as animpact evaluation of the benefits delivered throughIROR, rather it provides strong qualitative indicatorsof how valuable the programme will be to industry.

FindingsFeedback from the nine Participants on theanticipated business value of their individual projectsindicates that there is a solid commitment andenthusiasm to continue with the programme. Fromthe data gathering and analysis (See pages 11 - 17)the most important areas of anticipated impactidentified by Participants were improved outcomes in:

• Time to market / implementation• Skills dependency • Knowledge capture and retention• Reduced costs / improved resource efficiency

EXECUTIVE SUMMARY

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1Where the term ‘Participants’ is referenced in this report it refersto the nine organisations interviewed. For clarity, a further 11organisations remain engaged in the programme but are at anearlier stage in terms of assessing potential benefits.


Time to market /implementation was the highestrated likely future benefit. Theindividual drivers of this

advantage varied across the IROR programme, butexpectations included, greater productivity inresearch processes and improved predictability ofresearch time to business value. Anecdotally, thesegains are expected to be significant e.g.development time reduced from two years to twomonths in some cases. These benefits were cited by Participants of all sizes who form part of a numberof supply chains for goods and services oforganisation. Consequently, these expected impactsoffer the potential for scale up of productivity andeconomic benefits.

Skills dependency washighlighted as an early positiveimpact due to the high-qualityexpertise provided as part of theIROR programme. This includesdeep knowledge of artificial

intelligence (AI) and machine learning (ML). TheInCEPTTM process used for IROR industrialengagement, (see Appendix 2 – page 24), ensuresthese high-quality skills are applied more effectivelyto mutually-agreed, high priority, challenges with

lower business risk than alternatives options forskills acquisition (e.g. PhD studentships). Theeffectiveness of this data-intensive digital skillsenablement facilitated by the IROR projectsunderpins Participants’ enthusiasm andcommitment to the IROR programme.

Knowledge capture andretention was also highlyrated as an important sourceof potential productivitygains by enabling moreeffective use of research and

STEM talent to maintain and maximise competitiveadvantage. Participants believe this will be achievedthrough, firstly, enabling less skilled researchers tocomplete research tasks (now made more routine)and, secondly, by mitigating the risk of knowledgeloss through improvements in the transfer of skillsand knowledge to new STEM talent. It was alsorecognised that the introduction of the technologiesdeveloped in IROR will catalyse a more proactiveapproach to the management of data assets.

Reduced costs / improvedresource efficiency here thebenefits were projected to covera wide range of areas fromreduced testing costs (e.g.

materials, staff and high cost computing time),improved use of resources in operations of theproducts and in manufacturing processes.

EXECUTIVE SUMMARY (CONTINUED)

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Recommendations: The following recommendations are based upon ananalysis of the survey feedback and follow-upinterviews with Participants. These are described inmore detail within the main report (see page 21).

In summary, it is recommended that consideration isgiven to:

1. Instituting a mutually agreed monitoring andimpact evaluation process as part of individualIROR projects and the IROR programme.

2. Ensuring all IROR projects have the regularinvolvement of an executive sponsor from eachParticipant so that there is high level businessvisibility and support for the full adoption of thetechnology.

3. Establishing a more detailed and transparentunderstanding of the value of the digital assetsbeing developed by the Hartree Centre as partof IROR projects.

4. Identifying best practices that maximise theParticipant identified gains / benefits in:

• Time to market / time to implementation• Reduced costs / improved resource efficiency• Skills dependency• Knowledge capture and retention

Leveraging the lessons learned from IROR to establisha scalable enablement facilitated by the IRORprojects to the practical application of AI and ML.

EXECUTIVE SUMMARY (CONTINUED)

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This report, produced by Cambium, summarises thefindings of a qualitative survey of IROR Participants’progress and emerging benefits of the IRORprogramme. It examined the following areas:

• The level of support and commitment offered byindustrial collaborators to the IROR programme.

• The anticipated business value of IROR from theParticipant’s perspective to derive an earlyindication of the potential benefits of the projectin the context of their business, sector or thewider economy.

• The status of the IROR programme to supportthe development of ideas to create more valuefor all stakeholders as the programme evolves.

The Hartree Centre and the IROR ProgrammeThe Hartree Centre’s mission is to “transform thecompetitiveness of UK industry by facilitating andaccelerating the adoption of high performancecomputing, big data analytics and cognitivetechnologies”. In 2015, the Hartree Centre began aprogramme of collaborative work with IBMResearch called Innovation Return on Research(IROR) to deliver on this mission. The technologiesdeployed as part of this transformationalprogramme comprise state of the art techniques inartificial intelligence, big data analytics, computer

modelling and simulation, machine learning andvisualisation. These technologies are collectivelyreferred to as ‘data-intensive’ technologies withinthis report.

The role of the programme is to provide ‘proof oftechnology’ applied to business challenges as partof the process of translating research ideas fromearly Technology Readiness Levels (TRL) e.g. 1-3 tolater stages of the innovation process e.g. 4–7. As achallenge-led initiative, the programme looks toaddress areas where the complexity and level of riskof developing a successful technology solution istoo high for any single business or organisation toundertake alone.

Key to this programme is the engagement ofindustry partners to select business relevantchallenges, where the data-intensive technologiescan be applied.

These are then validated through proof of concept’’projects. This industry engagement process wasenabled and accelerated by a research translationprocess – called InCEPTTM (See Appendix 2, page 24for a process overview). This was applied to threechallenge-led domains:

• Science, Engineering & Manufacturing (SEM)• Chemistry & Materials • Life Sciences

Most projects are still at an early stage ofimplementation, so this report primarily refers tothe expected business benefits of the researchrather than to specific outcomes and impactsachieved so far. However, the programme hasalready enabled a clearer view of these potentialbenefits and in many cases the scope of individualresearch projects has begun to set up keymilestones to assess these anticipated outcomes. These projects follow a common three stagepattern of:

1. Testing the technology on a problem closelyaligned to a Participant’s business challenge, butwhere the test is conducted using open oranonymised data.

2. Completion of a custom test of the technologyusing the Participant’s private data

3. Assuming progress is maintained, thetechnology is then validated by a real-worldapplication or a pilot within the IRORParticipant’s operations.

INTRODUCTION

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From the work completed on the IROR programmeto date, nine organisations across the three domainareas (SOWs) and representing both SMEs andlarge-scale enterprises were interviewed using asemi-structured interview process based on a pre-set questionnaire template covering a broad rangeof business benefits.

The template was based on information gatheredfrom previous work within the InCEPTTM

engagement process and used as an initial guide toidentify the areas of greatest value for theparticipating organisations. These areas were:

1. Time to market2. Time to implementation / deployment 3. Reduced costs4. Reduced waste / improved resource efficiency5. Reduced carbon footprint6. Improved product / service features 7. Skills dependency8. Talent attraction and retention 9. Knowledge capture and retention10. Regulation – license to operate

Any areas identified as high value were discussedwith the Participant in more detail.

The scores were compared by overall areas ofgreatest/most important impacts to the business,by SOW domain and by individual Participant. Forcommercial confidentiality reasons, only theanticipated business value aggregated across allParticipants and by SOW are included in this report.

SURVEY APPROACH

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Data Centric Technology

Innovator

or Researcher

Global Challenges Business

DevelopmentIndustry exposure

to innovationRefined innovation

requirements

Real-world feedback

TechnicalExperts

Executive Sponsors

Accurate business case (ROI)

Agreed implementation

plan

Clarity on adoption risksTechnology Licensing

Spin Out

Bespoke development

Platform/Cloud as a Service

Exploration Insights Navigator Capitalisation

OPEN HYBRID PROPRIETARYDATA

Testing technical /scienceknow-how to address

challenge using public /anonymised data

Capture learningand validate

business impacttargets deliverable

Deploy technology onreal-world project to

assess and realisebusiness impact


• Time to marketDefined as the time taken from theproduct/service being conceived, toit being available to be promoted ina market or implemented andplaced into production.

• Skills dependencyParticipants are benefitting fromaccess to new high-level skillsrelating to the technologies beingused in the IROR programme.Participants are accessing skills andknowledge that are not availableinternally and reducing coststhrough not recruiting new skills(e.g. PhD studentships).

• Knowledge management &retentionKnowledge capture and retentionpractices vary between Participants.Nevertheless, this expertise is seen asbeing important to the businesscompetitiveness. Using knowledgeeffectively is recognised as apotentially fertile, untapped sourceof new products or services.

• Reduced costsThe technologies used within IRORare enabling higher accuracysimulations and more ‘intelligent’screening of research options. Bothproject outcomes are in turn offeringnew opportunities for optimisinguse of resources and reductions incosts.

SUMMARY OF SURVEY FINDINGS

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The survey results identified four significantareas of important early business value:


SUMMARY OF SURVEY FINDINGS (CONTINUED)

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Time to market / time to implementationSkills dependency

Knowledge capture and retentionReduced waste / improved resource efficiency

Reduced costsCorporate brand risk / enhancementMarket share / sales growth benefit

Talent attraction and retentionCost of compliance

Reducing the risk of breaching compliance Price point benefit

Supply chain dependenciesRaw material dependencies

Reduced carbon footprint

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

89%

67%

61%

61%

61%

56%

56%

44%

33%

28%

28%

17%

17%

6%

The bar chart below shows the ranked scores aggregated across all three SOW areas. The highest scores are highlighted in yellow:


SUMMARY OF SURVEY FINDINGS (CONTINUED)

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Science, Engineering & Manufacturing Chemistry & Materials Life Sciences

Time to market / time to implementation 100% 75% 75%

Skills dependency 60% 75% 75%

Reduced costs 60% 75% 50%

Reduced waste / improved resource efficiency 70% 25% 75%

Knowledge capture and retention 60% 75% 50%

Market share / sales growth benefit 40% 75% 75%

Corporate brand risk / enhancement 30% 75% 100%

Talent attraction and retention 30% 25% 100%

Cost of compliance 30% 50% 0%

Price point benefit 40% 0% 50%

Risk of breach 30% 50% 0%

Raw material dependencies 30% 0% 0%

Supply chain dependencies 30% 0% 0%

Reduced carbon footprint 10% 0% 0%

The scores provided by each Participant were aggregated by each domain area (SOW). The table below shows thecomparison of likely / perceived benefits across all three domains:


This section analyses the overall level ofengagement of the Participants in the IRORprogramme and the highest-ranking anticipatedbusiness benefits. This section also highlights theimplications for how these anticipated sources ofvalue may be developed in the remainder of theIROR programme.

1. Engagement of IROR Participants

Overall IROR Participants, particularly at a technicallevel, remain enthusiastic towards both theprogramme and the potential benefits that mayresult. However, broader commitment involvingmore commercially focused colleagues and businessdecision makers is currently limited, particularly inlarger Participant organisations.

Implications• More involvement of commercial colleagues and

business decision makers would furtherstrengthen the validation of IROR benefits foreach Participant. This increased sponsorship alsoimproves the likelihood of successful projectsthat apply IROR technologies being commerciallyimplemented within a Participant business.

ANALYSIS OF SURVEY RESPONSES

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ANALYSIS OF SURVEY RESPONSES (CONTINUED)

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2. Time to market / time to implementation

This relates to reducing the time it takes to get newproducts to market or, reducing the time toimplement upgraded versions of products in activeuse. Time to market and implementation is the mostimportant potential benefit from the IRORprogramme according to the research. Eight of thenine of Participants in the survey cited this as beinglikely to have a high impact on their business, withall interviewees confirming its importance.Participant feedback also reflected differences inmarket sectors and competition dynamics in the waythe data intensive technology was being applied.

Some IROR Participants are improving the deliveryof their products for a single public-sector clientwithin a long-term capital-intensive programme.Here innovation advantage is anticipated fromimproved operational performance or throughextending the lifespan of in-service components.This was particularly important for Participantsoperating in heavily regulated sectors, where anynew or upgraded components must meet stringentstandards before they can be adopted foroperational use.

For other Participants, better screening of researchcandidates and more accurate simulations offer thereal potential to improve researcher productivity.This uplift in researcher productivity is expectedfrom improved predictability in the lead time for thedevelopment of new IP. For example, in LifeSciences, the Participants anticipate a reduction inthe list of ‘promising’ candidate antimicrobial agentsto be put forward for further development.Similarly, some Chemistry & Materials Participantsanticipate benefit from better candidate materialsidentification. In this case the benefits would comefrom a reduction in mandatory regulatory testing.

Implications: • Time to market / time to implementation has

potential to be a universally applicable evidencepoint of impact for IROR. It points to potentialgains in both productivity and market advantage.

• The technologies have the potential to providebenefits across a range of sectors. In particularthose where development costs are significantand where customers value faster or morepredictable development times for newproducts. This potential value is already visiblefor Participants operating in markets where newinnovations are subject to strong regulation.

• This business value therefore merits closeattention so that the benefits of the programmecan be monitored for progress. Markers such asthe status of internal implementation or productlaunch project plans could be used as a proxy tomonitor the level of progress and effectiveness.



3. Reduced skills dependency

This was seen as a strong benefit area across all threeSOWs with five of the nine Participants scoring it ashigh impact and a further three as medium. AllParticipants cited the benefits of their organisationgaining early access to new skills relating to thetechnologies offered by the IROR programme.

The Participants noted the high quality of staff withrelevant experience in advanced technologies, (e.g.Uncertainty Quantification or UQ), that was notavailable within their own organisation withoutfurther investment (for example, by funding a PhD).

The skills accessed via IROR were recognised asbeing of superior quality to those typically providedby a PhD student and equivalent to those in specialistcontractors. These skills are rare and not readilyavailable through the contractor market, as yet.Provision of these high-quality skills within IRORwas seen as reducing the time for Participants toevaluate how these new, emerging techniquescould be applied to their business challenges.

Participants indicated that the combination of highquality skills and experience in data-intensivetechniques being applied to their recognisedbusiness challenges was enhancing the likelihood ofwider adoption of these innovative technologiesinto their business.

Several Participants quantified the costs andidentified the risks of alternative modes of acquiringthe skills and knowledge provided within IROR. Formost Participants, the primary alternative is fundinga PhD student – over 4 years this is estimated to becost circa £100k. This does not include any:

• Quantification of the benefits of a researchproject focused on their challenges, wherebusiness benefit can commence immediately

• Estimate of the search costs for finding auniversity supervisor and student capable ofcompleting a similar project

• Consideration of the risks and time delay to valuedelivered that were experienced through academicdeviation from agreed industrial priorities

Overall, the deployment of specialist skills withinthe IROR programme is providing early value to theParticipants by enabling earlier and more effectiveadoption of innovative data-centric technology. Itrepresents a tangible cost saving over alternatives,such as providing the equivalent of a PhD level one-person allocation per participating organisation.

In terms of overall value, the IROR Programme ishelping to accelerate strategically importantprojects which may not have otherwise progressedin the near term. The programme is helpingParticipants commit earlier to building their artificialintelligence skills, which also contributes to thebuilding of skills capacity in this emergingtechnology within the UK economy. This case forskills development though IROR is likely to becomestronger as Participants further realise theanticipated business value from their projects.


3. Reduced skills dependency

Implications: • IROR is already delivering effective skills

development via the introduction and earlyadoption of data-intensive technologies.

• IROR provides Participants with a more effective,lower-risk alternative to university PhDstudentships, at a significantly lower cost.

• The collaborative innovation process deliveredthrough IROR has the potential to be used toaugment the artificial intelligence and machinelearning knowledge of existing PhD students.

• The IROR programme has the potential to play abigger role in the faster scale-up of scarce AI/ML skills in the UK economy. This could beenabled by further collaboration with otheracademic institutions and PhD programmes byenabling recent post-doctoral personnel toacquire experience in the application of data-intensive technologies to real world businesschallenges.


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4. Knowledge capture and retention

Knowledge capture and retention is expected tohave a high level of business benefit by five of theParticipants and medium impact by a further two.Knowledge capture and retention practices varybetween companies, but it is generally seen asbeing important to the maintenance of businesscompetitiveness and a potential source of highproductivity gains.

Projected benefits for SEM Participants included:

• Using the specialist expertise available withinIROR, Participants can tap into and get evidenceof the value of UQ techniques earlier and withlower risk. The ability to accelerate the valuederived from UQ techniques without divertingtheir own valuable resources from existingpriority projects is seen as a significant source ofearly value.

• For capital-intensive businesses, where theoperational lifespan of custom-built plant andequipment is measured in decades, the captureand retention of knowledge is vital. Even moreso when there is a shortage of skills andexperience in data-intensive technologies withinthe business and wider economy. ManyParticipants face a knowledge retentionchallenge caused by the retirement of many ofexperienced engineers. These individuals oftenhave detailed and unique knowledge of olderplant infrastructures. In response, manyorganisations are implementing programmes ofinternal knowledge transfer, augmented by anaggressive programme of PhD recruitment. IRORprojects offer the opportunity to use artificialintelligence and other data-intensivetechnologies as a vehicle to transfer skills from

the more experienced staff. Successful resultsproduced in the IROR projects are expected tocontribute to this retention of key organisationalknowledge by incorporating outcomes intothese training programmes.

• The use of machine learning within IROR is alsohelping the capture and retention of key knowledgewithin the organisation. This technology offers thepotential to enable less experienced engineersto make more progress with less supervisionusing new design tools that can access retainedknowledge acquired in previous projects. Thisapproach also frees-up more experiencedengineers to tackle unsolved problems that aremore challenging and of potentially higher value.

• For SME Participants, recruiting good people andgetting them ‘up to speed’ and workingproductively quickly is vital to sustain growth.Some of the tools being developed by theprogramme offer the potential for smallerorganisations to reduce their reliance on smallernumbers of key in-house personnel forknowledge transfer. The use of this technologyoffers the potential to improve the overall valuesuch organisations can produce by making moreof their existing knowledge and expertise.


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4. Knowledge capture and retention

For the Participants in the Chemistry and MaterialsSOW, the impact of knowledge capture andretention was rated low – medium although, it wasacknowledged that the programme creates apositive pressure to develop better methods ofinternal data management.

Knowledge capture and retention was seen as ahigh impact area for Life Sciences businesses withParticipants seeing this as a major area of expectedbusiness value through the generation of more newproducts and licensing opportunities.

Implications: • Better ways to manage and retain key

knowledge is recognised by all Participantsacross all SOWs as an important potentialenabler of business sustainability andcompetitive advantage. This value is importantto businesses irrespective of their scale or size.Productivity benefits are projected from betterknowledge management through:

• Enabling the more effective use ofresearchers by empowering less skilledresearchers to complete more research tasksaided by machine learning tools.

• Evolving better ways to mitigate the risk ofknowledge loss from ageing workforces byfinding better ways to transfer skills andknowledge via learning and potentially to actas an attraction to new STEM talent.

• ‘Freeing up’ more experienced staff toaddress higher value / more complexchallenges.

• Providing an increased focus on themanagement of each organisation’s data assets.

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5. Reduced costs

Reduced costs were anticipated as being a high ormedium impact by seven out of nine of theParticipants. The technologies used within IROR areenabling better starting points for research throughmore ‘intelligent’ identification and screening ofcandidate options. This has the potential tosignificantly reduce associated costs by enabling:

• More accurate proofs of the operationalperformance of existing components - reducingthe need for real-world testing and extendingthe time between scheduled maintenance orreplacement.

• Improved screening of alternative candidatesolutions to reduce testing volumes.

• Improved use of resources in manufacturingprocesses.

• More efficient use of the high-performancecomputing infrastructure through reduced oroptimised cycle times.

As an example, projected benefits for SEM includedimproved virtual testing of components throughhigh accuracy simulations using techniques such asuncertainty quantification (UQ). The resultingimproved accuracy of computational fluid dynamics(CFD) simulations contributes to lower costs byoptimising designs earlier in the developmentprocess. This in turn results in improved plantperformance and extension of the time periodsbetween scheduled maintenance. IROR is alsoexpected to improve understanding of theoperational performance dynamics of existingcomponents enabling an overall system to useavailable resources more efficiently.

The high accuracy simulation projects with an UQcomponent offer the potential to secure significantsavings in testing costs, particularly in heavilyregulated environments where the standards ofproof required to extend the working life ofcomponents is high. In this context asset lifecycleextensions testing can cost in the region of £0.5m.The impact of reduced costs also extends to thedesign and construction of new facilities. The costssavings involved here, particularly for large capital-intensive projects are likely to be of the order ofseveral millions or tens of millions of pounds.

The IROR programme is also expected to result inbenefits through the optimisation of the computingresources needed to complete a simulation and thenumber of simulations required to get valuableoutputs. These benefits can be taken as reducedcosts and/or allowing more computing time forother important projects. Improved UQ techniquesin simulations is also providing a betterunderstanding of production tolerances, reducingwaste and reprocessing costs.

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5. Reduced costs

In Chemistry and Materials projects benefits includedimproved screening of candidate product materialsto reduce the need for testing. For instance, toxicityand biodegradation testing for a new chemicalformulation typically costs £10k-20k. For Life Sciences, the benefits are similar to theChemistry and Materials companies. Candidatematerials in this sector can be expensive tosynthesize costing several thousands of pounds fora few grams. Generating candidate materials is avital and expensive step in the research anddevelopment process. IROR Participants expect asignificant cost reduction through the betterscreening of candidate materials. This will lower thecost barriers in generating new products andlicensing opportunities.

Implications:• A cost-benefit analysis generated from IROR

projects can help Participant organisationsbetter understand the returns on investment inthese new technologies and allow their value tobe assessed against alternative investmentopportunities for the business.

• The programme could provide useful insightregarding the improved efficiency of IT facilities.Specifically, in the use of HPC and thedeployment of data-intensive technologies.

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This survey confirms that IROR Participants expectthe programme to deliver positive benefits for theirbusinesses with the most important areas being:

• Time to market / time to implementation• Reduced costs / improved resource efficiency• Knowledge capture and retention• Skills dependency

Participants and stakeholders can increase the valuethat they derive from the IROR programme, byimproving the overall governance of the IRORprogramme as follows:

1. Business value monitoring:

Institute a mutually agreed monitoring process, aspart of both individual IROR projects and the widerIROR programme.

The early positive indicators of likely impact canprovide an important source of learning andunderstanding of the potential value of the IRORtechnologies across a range of domains. A greaterunderstanding of the mechanisms by which thesetechnologies can catalyse new sources of businessand economic value will benefit Participants, theHartree Centre and the UK economy.

Acquisition of these insights will require aconsistent mechanism to monitor benefits andvalue within the IROR programme. This monitoringwill foster a deeper understanding of the high-levelbusiness benefits and can provide information toassist with estimating the economic value that maybe accrued from the use of these technologies.

2. Increase executive sponsorship within IRORprojects

Ensure all IROR projects have the regularinvolvement of an Executive Sponsor from eachIROR Participant to provide feedback andmentorship relating to programme implementation.Given the potential positive benefits resulting fromparticipation in the IROR Programme, it isrecommended that an Executive Sponsor for IROR isappointed by each Participant organisation. Theprecise details of this role need discussion withIROR Participants, but typically may include:

• Review and feedback on bi-annual reports onprogress within their IROR projects

• Receiving updates on the general insightscaptured and shared amongst all Participantsresulting from the metrics monitoring process.

• Identification of business risk(s) from thedeployment of IROR projects and to ensure thatmitigation plans could be created at aParticipant and IROR programme level.

• Validation of business benefits identified withineach project and to determine which of thesebenefits that could be shared more widely.

This high-level business visibility also provides theopportunity to raise awareness and understandingof the potential sector impact and therefore therisks of the ‘do-nothing’ option. That is, what arethe implications if other businesses develop andapply this type of technology.

3. Assessing the value of IROR digital assetsEstablish a deeper understanding of the value of thedigital assets being developed as part of the IRORprojects.

IROR Participants may improve the value theyderive from the IROR programme via a greaterunderstanding of how the digital assets developedby the Hartree Centre are enabling business valuewithin their projects. This deeper understandingwill enable the Participants to provide feedbackthat can help focus Hartree Centre resources ontodigital assets that are adding most business valuewithin the projects.

RECOMMENDATIONS

21


A better appreciation of the impact of digital assetscan also enable Participants to identify opportunitieswhere the faster or additional development ofdigital assets could deliver even greater positiveimpact, business value and increased productivityacross the overall IROR programme.

4. Best practices in the use of data-intensivetechnologies

By identifying best practices that maximiseproductivity, it is expected that Participants, theHartree Centre and wider stakeholders can obtain abetter appreciation of the common patterns andtrends relating to how the IROR technologiesimpact business value and potential productivityimprovements. The effect of improved governanceand monitoring can deepen their understanding ofhow the technologies are creating these impactsand inform the strategic direction of digital assetdevelopment.

In relation to each of the most important benefitareas, this knowledge will help to improve theoverall understanding of:

• Time to market / time to implementationIdentifying high potential areas where furthercompetitive and comparative advantage may becaptured through use of the technologies.

• Knowledge capture and retentionCapturing and disseminating lessons learned byParticipants to develop knowledge capture bestpractices.

• Reduced costs / improved resource efficiencyIdentifying new areas of cost savings enabled bythe programme, e.g. best practice in theoptimisation of expensive HPC infrastructure usage.

• Skills dependencyCapture and disseminate lessons learned byParticipants during the IROR programme, thataccelerate skills acquisition and development, e.g.through case studies describing the skills acquisitionbenefits relating to the adoption of data-centrictechnologies.

Next steps:In support of the recommendations above, theHartree Centre should build upon the earlyanticipated benefits of the IROR programme bysecuring the input and buy-in of IROR Participantsto an ongoing IROR governance programme. Thiswill ensure that progress is maintained during theremainder of the programme so that the earlybusiness value documented in this report isconverted into tangible outcomes and impact thatwill benefit all programme stakeholders.

RECOMMENDATIONS (CONTINUED)


SCIENCE, ENGINEERING & MANUFACTURING (SEM)The overarching vision for this programme is thecreation of a ‘digital’ or virtual twin for physicalcomponents or systems. This requires the ability toextend the existing digital modelling capabilities toaccommodate different length and time scales(multi-scale) and combine different engineeringscales (multiphysics), e.g. deal with systemsinvolving solid, liquid and gas interactions at theatomistic level through to the metre length scale. Tobe meaningful, all this needs to be achieved with adegree of accuracy to match the ‘real world’ twinand therefore would require ongoing validationand verification).

CHEMISTRY & MATERIALSDevelopment of an integrated data analytics,modelling, and simulation capability able to addressa broad variety of chemical and materials problemswith world-class scale and accuracy.

LIFE SCIENCESAnti-Microbial Discovery (AMD) work consists ofthree integrated workstreams which combinedcreate a ‘learning loop’ for accelerating anti-microbial discovery by better targeting of the mostpromising candidates through simulation andcognitive techniques.

APPENDICES

23

APPENDIX 1 – Statement of Work (SOW) Models

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APPENDICES APPENDIX 2 – The IROR Industrial Engagement Process – InCEPTTM

DISCOVERYMatching Research

Capabilities to Business Challenges

TECHNICALVERIFICATION

Validating Scope toBusiness Specific Needs

BUSINESS VALUEVALIDATION

Assessing progressagainst Business Benefits

BUSINESS VALUEREALISATION

Range of exploitation options

Innovator

or Researcher

TechnicalExperts

Executive Sponsors

Technology Licensing

Spin Out

Bespoke development

Platform/Cloud as a Service

Exploration Insights Navigator Commercialisation

OPEN HYBRID PROPRIETARYTYPES OF DATA

Mapping of Researchcapability to identify

potential business value

Jointly agreed metrics tomeasure progress aligned

to business value

Collect, analyse and sharebenefit areas and drivers

of impact

Testing technical /scienceknow-how using public

/ anonymised data

Capture learning andvalidate business impact

targets deliverable

Deploy technology onreal-world project with

real world data

Domain experts

Innovation Leader

BUSINESS VALUE /IMPACT VISIBILITY

Eco-Innovation CentreCity Road

PeterboroughPE1 1SA

+44 (0) 8456 383 280

www.cambiumllp.com

mid term –participants survey review hartree centre...statements of work-relating to each of the...

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