HESPA Conference 2020 – Day 1 PM

Workshop 4 – The Analytics Translator: Reflections on this role in the UK HE context by Manchester Metropolitan University

The analytics translator came from a Harvard business review article. MMU have applied it to the ir planing unit. It bridges the gap between data scientist and business leaders, designed to ensure that insights are generated in an appropriate form. shared with stakeholders and applied to enhance key business areas. So that makes perfect sense. These folks support the faculty of Business and Law.

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Here’s the process.

Translator process

This approach is really labour intensive so a great example of resource deployment at institutional level. At national level at Jisc we can help with the heavy lift through those complementary services:

1. Analytics labs – unique continuing professional development (CPD) experience available to data-savvy staff in education
2. Data consultancy – A bespoke consultancy service to support you in using HESA data to answer your key questions.
3. Tailored data sets – Custom HESA data and reports built to your exact requirements. We’ll work with you to design them so you get exactly what you need.
4. Interactive Insights dashboard development for service delivery – NEW! Here’s the first of these – a full suite of 17 dashboards supporting a specific theme, in this case the workforce explorer

Business sessions – ALTIS – How to get senior leadership alignment around data and analytics via a strategy and roadmap engagement.

This is a commercial outfit with experience in data road map development for Higher Education Institutions. They have a recipe they follow with key senior management stakeholders. A show of hands at the start demonstrated a 50/50 split of low maturity in this area, high maturity, but only a handful claimed a shared and mature vision about data strategy at senior management team. These guys are vendor independent.

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Once these areas were identified a benefit / feasibility matrix provided the low hanging fruit (high benefit / high feasibility quadrant ensuring the project gained maximum visibility quickly with benefits realised.

Here’s the roadmap agreed upon by the Aberdeen University project team

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The entire piece took 6 weeks so very labour intensive, though the client (Aberdeen University) felt this was super quick. It provided compelling evidence for a business case and got the organisaiton ready for the next phase of implementation. The workforce became more enthusiastic about data as they acquired the benefits. The whole process was one of facilitation and knowledge transfer so Altis gradually withdrew as Aberdeen increased capability and capacity.

Final Plenary – Data Governance in US Higher Education – Aaron Waltz Purdue University
I worked with Aaron and Hank Childers from the US Higher Education Data Warehousing Forum on a national Business Intelligence Maturity study some years ago and last met them at the Educause Conference I was co-Chair at in 2015.

So that was nice….

Aaron poses the question – why data governance – what’s that about then? He uses the example of staff count and how difficult that is to answer. HEDW has 4000 members and data givernance has been the top issue for the last four years. So that mirrors the CK UCISA CISG survey. Here’s the US survey result. The UK survey was very similar across 50 responding Universities.

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Chief Data Officer as a role is gaining traction in the US. Aaron went n to discuss the Data Governance programme under their Chief Data Officer at Purdue. Common data definitions (Data Dictionaries in the UK) and improving data quality were key tenets. The initiative has no end and recognises that it cannot achieve without buy in from all staff so is top down and bottom up. Data Cookbook was used for the data definitions as it’s designed for Higher Ed use. and with a sense of superb timing I just got spammed by them. They used to give away data spatulas as part of their conference swag but I can vouch that they melted if used in earnest but from this talk I can vouch that the product itself is much more robust!

Purdue have public facing dashboards showing relevant performance to their immediate community. They also have management information dashboards. Here’s a shot of some of those

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Look familiar?

Aaron suggest asking ‘are we ready for a long uphill climb?’. Data governance is a means to an end. The end should be what are the questions our leaders need to answer, nit just standardising definitions. Don;t try to define everything, just pick some quick wins. It’s a long haul.

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