Future ready research teams: are we there yet?

Malcolm Wolski, Director, eResearch Services, Digital Solutions (Presenter)

Dr Michelle Krahe, Senior Research Fellow, Health Executive

Dr Joanna RIchardson, Library Strategy Advisor, Library and Learning Services

How we got here

What is a “research team”? • It has a team leader (e.g. PI, senior researcher, centre director)• Team members undertake key roles such as data management and

analysis, stats, research admin, writing up findings (i.e. team members have understood roles)

• It can cross institutional boundaries

• Initiatives targeting digital literacy/skills

• Increasing engagement at the team level

• A strategic goal to benchmark eResearch

capability of specific research groups

Measure digital capability

Some observations • Digital capability varies widely from

team to team• Teams can change in size and

capability quite quickly• Scale issues• Coding and DM practices immature

• Manual processes• Gap between intention and practice

• Cultural issues• Teams produce most research outputs

Where are we?Drivers

Pace of technology change

ScaleComplex research problems

Experience with new techNew performance metrics

DX in Industry

University

Digital Transformation agenda (DX) L&T and business hot topicsResearcher skills targeted

Skills?Digital thinking?Time?

Adaptability?

Research Team Performance

What we looked at

○ What DX models are in the literature

○ How do they translate to the operational level

○ Applicability for research team environment

○ How to apply the model

What we wanted to know

o How do you assess team digital capability

o How do you gauge agilityo Is there a framework or model we

could use for thiso How could we use it to improve

services

Dimensions of DX in organisations

Customer

Technical Integration

Culture

WorkforceContinual Assessment

Leadership

Key findings:

• Pace at the operational level is too slow

• Commitment to “digital” weakens

below the executive level • Leaders struggle with the operational

changes required

• No useful models and frameworks

• Five dimensions of DX

• Customer is at the centre

Research Goal vs Customer?

Operational Capabilities

• Information Management

• Technology infrastructure

• Process Agility

• Analytical Techniques

• Governance

Digital Transformation at

the Research Team level

Assessment scale

https://library.educause.edu/resources/2017/9/digital-capabilities-in-higher-education-2016-analytics

Absent EstablishedDevelopingInitial Optimised

INFORMATION MANAGAMENTDocumented workflows for

handling and managing data

Regular data cleaning/archiving activities are undertaken

Documented SOPs for handling and processing sensitive data

Agreed IP and licensing in place for the team data outputs

Long term data sharing agreements

Understanding of relevant legislation & info/cybersecurity

IM roles and responsibilities assigned

Regular review of available data sources to improve the overall data

resource capability

Absent EstablishedDevelopingInitial Optimised

TECHNOLOGY INFRASTRUCTUREDocumented workflows for

handling and managing data

Use of a code repository that manages in-house software code

(doco and version control)

Existence of an information technology plan to achieve research

goals.

Processes address cyber/information

security issues appropriately

Right level of ICT skills and knowledge to be able to discuss

and understand infrastructure issues

Right software applications and infrastructure for the scale and

speed of data

Absent EstablishedDevelopingInitial Optimised

PROCESS AGILITY

Workflows integrated into a seamless process

Workflow take advantage of new software and technologies.

Documentation & understanding of core data workflows

Open standards with loosely coupled processes

Existence of a information technology plan to achieve research goals.

Processes address cyber/information security issues appropriately.

Workforce plans addressing skills and knowledge for processing data

Awareness of info/cybersecurity in practice

Plans in place with external groups to promote ongoing process

development

Absent EstablishedDevelopingInitial Optimised

ANALYTICAL TECHNIQUES

Plans to reduce manual intervention in the analysis processes and more

integrated data flows

Code repositories in use to manage code produced within the team

A published long-term vision of the analytical capability (skills and tools)

Agreed IP and licensing methods in place for any team code outputs.

Plan to develop the appropriate level of analytics skills to meet

future research outcomes

Allocated time to research, test and demonstrate new data opportunities

and analytical techniques.

Absent EstablishedDevelopingInitial Optimised

GOVERNANCEHigh level documentation of all current technology solutions

utilised and workflows between

Procedures and guidelines for data & code in place

Catalogue of data assets maintained

A data management plan underpins the research goals

Risk management plan for data and technology

A workforce plan to develop digital capabilities to achieve the

research goals

Plans and processes to continually review emerging processes, methods

and technologies

• Targeting one indicator can improve others

• Research teams can also outsource, e.g. Ø external partner expertiseØ external facilities/services (e.g.

NCRIS projects)Ø within the institution (libraries and IT)

SO WHAT• Experienced staff already judge the capability of research teams

• Needs to be fit for purpose (scale and discipline)

• Where might my service target specific gaps • Fill a technology shortfall (storage, GitHub, repository) • Help develop team skills and capability (training in coding, DM practices)• Fill a short term gap (coding, help with metadata, catalogue data held)

• How could my services be used to lift team capability (prioritised)• Partner at some defined level for a period of time to meet a predefined objective (e.g. embed

metadata expertise to upskill a team or a programmer to build sustainable data workflows)• Combine service provider expertise in a program to improve DM practices (e.g. develop

repositories, standards, workflows, coding practices) • Target joint grant/funding proposals to fill gaps and execute if successful• Be a heavy technology partner until only a light touch is needed to lift team capability (i.e. plan

your way in and out)

Is it useful for:○ A Checklist approach

○ Changing the nature of the conversation with research team leaders ??

○ Benchmarking ???

This Photo by Unknown Author is licensed under CC BY-NC-ND

Some referencesAsia-Pacific Economic Cooperation (2017), “10 recommended APEC data science & analytics competencies”, APEC, Singapore, available at: https://www.apec.org/Press/Infographics/10-Recommended-APEC-Data-Science-and-Analytics (accessed 25 September 2018)

Holden, L., Pager, S., Golenko, X. and Ware, R. S. (2012), “Validation of the research capacity and culture (RCC) tool: measuring RCC at individual, team and organisation levels”, Australian Journal of Primary Health, Vol. 18 No. 1, pp. 62-67.

Holewa, H., Wolski, M., McAvaney, C. and Dallest, K. (2015), “The HWMD maturity model: a foundational framework to measure effectiveness of institutional research e-infrastructures”, paper presented at THETA 2015, 11-13 May, Gold Coast, Australia, available at: http://hdl.handle.net/10072/69204 (accessed 25 September 2018).

Galanek, J. D. and Brooks, D. C. (2018), “Supporting faculty research with information technology. Research report”, EDUCAUSE Center for Analysis and Research, Louisville, CO, available at: https://library.educause.edu/resources/2018/6/supporting-faculty-research-with-information-technology (accessed 25 September 2018).

Gunsberg, D., Callow, B., Ryan, B., Suthers, J., Baker, P. A., & Richardson, J. (2018). Applying an organisational agility maturity model. Journal of Organizational Change Management, 31(6), 1315-1343.

O’Brien, J. (2018), “Digital transformation and technology narratives”, EDUCAUSE Review, Vol. 53, No. 2, pp. 4, 6, available at: https://er.educause.edu/~/media/files/articles/2018/3/er182103.pdf (accessed 25 September 2918).

Solis, B. (2016), “The six stages of digital transformation”, available at: https://www.prophet.com/thinking/2016/04/the-six-stages-of-digital-transformation/(accessed 25 September 2018).

Vey, K., Fandel-Meyer, T., Zipp, J. S. and Schneider, C. (2017), “Learning & development in times of digital transformation: Facilitating a culture of change and innovation”, International Journal of Advanced Corporate Learning (iJAC), Vol. 10 No. 1, pp. 22-32.