Business Intelligence for Strategic Planning

A picture speaks a thousand words

Dave SmithData Manager (Earth Sciences)d.a.smith@nhm.ac.uk

European Axiell Conference, Glasgow, UK May 2018

Biography

• Team of 6 in Collections Management Systems Division– Earth Science Data Manager

– ‘Fingers in lots of other pies’

• Support users to do their job efficiently– Manage and administer the CMS, its content and integrations.

– Training (classroom / 1 to 1 / online / documentation)

– Development to meet needs of collections management

– Perform large scale data cleansing

– Provide tools and advice on workflows to deliver digital projects

• Departmental EMu administrator since 2006

• Geological curator for 22 years

A picture speaks a 1000 words

Powerful imagery

© Mike Wells

Text vs visuals

• We each have different learning styles, with a preference of one of:– Auditory– Visual– Physical

• Human brain can process imagery upto 60,000 times faster than text.• 40% of nerve fibres to the brain are connected to the retina.• Whilst it is believed that human communication has existed for 30,000 years,

written communication has only been around for 3,700 years.• So humans more receptive to visual methods of communication – traffic

signs; facial expressions, body language.

What is Business Intelligence?

• Business intelligence (BI) leverages software and services to transform data into actionable intelligence that informs an organisation’s strategic and tactical business decisions.

• Business intelligence is also called descriptive analytics, in that it describes a past or current state. “It doesn’t tell you what to do; it tells you what was and what is.”

Mary K Pratt - https://www.cio.com/article/2439504/business-intelligence/business-intelligence-definition-and-solutions.html

Business Intelligence Dashboard

http://datapine.co.uk

BI in Museums

KPI Reporting

Making our data work for us

Current challenges

• Recurrent adhoc requests for information about business processes.– Individually tailored reports

• No single line of communication.– Different results from different people.

• Variable ease of access to the reports.– Maintained and archived on different file-shares.– Different formats make it difficult for comparisons

Business Insights Project

• Provide staff with ‘answers to common questions’– ‘Self-service’ reports from a single source

• 3 Dashboards• Customer Dashboard

– Analytics relating to website– How many visitors connect up to our WIFI– No. of visitors to ticked events– Time spent in galleries– Map visitor pathways to inform masterplanning

• HR Dashboard• Science Dashboard

– Access and downloads from Data Portal– Downstream impact of data access– Key Performance Indicators– Compliance– Collections Management

Collections Dashboard

Meaningful Metrix

Audience Purpose MeasureDirector & Trustees Business performance indicators 1. Progress towards strategic goal

2. Performance to FundersScience Director Business performance indicators 1. No of specimens digitised

2. Cumulative count towards strategic goal

Registrar Compliance to P&PBusiness performance indicators

1. Loans & items to UK and international venues.2. No. of acquisitions and items.3. Count of non-compliance (loans, acquisitions, disposals)

Head of CollectionsPCiCSCiC

Project ProgressConnect with Museum goalsIdentify data gapsStrategic planning

1. Count of new catalogue records.2. Data completeness3. Compliance of new & existing records.4. No of acquisitions & items5. No of loans

Data Management Team Identify data gapsIdentify inconsistencyMeasure complianceReport activity

1. Compliance of new & existing records.2. Data Completeness.3. Average time taken to progress records to approved standard.4. Effect of data cleansing

DCP Programme Project ProgressMeasure data qualityDownstream scientific impact

1. Count of new specimen records.2. Count of specimens imaged.3. Data quality of new & existing records.4. Count of cited specimens

EMu Users Project ProgressConnect with Museum goalsBusiness performance indicators

1. Count of new specimen records.2. Count of specimens imaged.3. No. of acquisitions and items.4. No. of loans; Overdue loans

Collections Dashboard - Goals

• Provide senior managers with consistent KPI figures– Single data source– Provide the context behind top-level figures.– Caveat – any inaccuracies will be consistent

• Provide staff at all levels with a tool to be able to answer common questions

• Be able to use the data to more effectively develop strategic plans– Gap analysis completeness– Compliance to policy– Prioritise data cleaning

• ?Be able to analyse cause and effect of business processes– Has publishing images on the Portal caused the number of physical loans to decrease?– Has improved digital discovery been shown to increase collection use?

Data completeness

Concept Description Data requirements

No Record No catalogue specimen record exists in the CMS None

Placeholder Minimum required to be able to capture data about an item e.g. name, condition report, location.

Unique ID

Inventory Compliant with NHM Collections Development Policy. Minimum required for an item to be findable by a new curator using the data in the CMS.

+ Taxon (to Class/Family)+ Location to room level

Core Compliant with NHM Collections Access and Information Policy and accreditation requirements.The minimum requirement for digital discovery (internal & external), WITHOUT the need to rely on labels/slips/registers.

+ Taxon (to Genus/Species)+ Location to cabinet/drawer level+ Site+ Collector & date

Enhanced Core data enhanced with digital media, analyses and other data relevant to the research discipline.No further need to refer to the paper inventories/ registers/ labels/ slip indexes.

+ Identified By+ Images+ Analyses

My new addiction

Demo

Digitisation Progress

Digitisation Efficiencies

Completeness Review

Completeness Review

Explore Collections Make-up

Loans and items sent to UK and International Venues

Loan KPI

Loans Due for return

Data Cleaning

User Activity Report

Glossary

• Dashboard– Consolidation of top-level figures

• Reports– Contextual analysis

• Data Tables– Structured data to feed visualisations

• Data Source(s)– Authority sources of data tables

Join the Dots

Deception

Images copyright © Erik Johansson (http://www.erikjohanssonphoto.com/)

Considerations

• Data structure– Different structures required to answer specific questions– Normalised star schema is recommended.

• Data cleanliness– Barrier to some visualisations (e.g. dates)– Poor integrity between linked visualisations– Ongoing inconsistency

• Scalability– Large data sets and complex formulae– Summarised tables– Manual exports automation

Benefits

• Microsoft Power BI desktop is free (n.b. other products are available).• Very well documented

– MANY online tutorials and videos• Low technical knowledge - accessible software.

– Familiarity with MS Excel formula and Power Query will go a long way.– Large datasets and sustainable model / queries may need best practice in data

architecture, MySQL and ‘M’, ‘R’ programming.

• BI tools will vastly improve communication about status – past and present.• Should replace production of individually tailored adhoc reports.• Dynamic nature of visuals allows for cross-querying.• Potential to connect different datasets to explore patterns/trends.• Powerful tool to help inform planners and decision makers.

• The NHM look forward to improved integration to Axiell products via RestAPI.

Potentially useful visuals

• Efficiencies• Data violations• Registry• Admin Tasks• Process alerts

Dashboards on the go!

Dave SmithData Manager (Earth Sciences)d.a.smith@nhm.ac.uk