2016 Digital Technology Discussion: Strategies, Trends, Future Visions
-
Upload
dhegley -
Category
Technology
-
view
311 -
download
0
Transcript of 2016 Digital Technology Discussion: Strategies, Trends, Future Visions
1
Digital Technology in
Museums & the Cultural Heritage Sector 2016
Discussion:
Strategies, Trends, Future Vision
Douglas Hegley
@dhegley
2
Technology: Tools to accomplish goals
3
Topic Trends and Questions Tools, Approaches, Methods
Audience-first Big Data, Participation and personalization, Omnichannel Salesforce, Tessitura, apps, platform
integration
Content Storytelling, Content layering, Context-triggered delivery Cross-functional teams, Responsive web tech,
Griot, OSCI, Location Based Services
Leadership Lean, Agile, Open, Radical Servant leader model, Self-organized teams,
Scrum
Workforce Flatter Org structure, Innovative hiring, Work-Life balance,
Disciplined collaboration
Small World Networks, Culture-based hiring,
Liquid workforce, Consortium model
Technology Cloud v. On-premise hardware, Mobile-first, Open source v.
commercial software, Content management
AWS, VM-Ware, HTML5, Github, DAMs, ECM
ecosystem, APIs
Impact Formal evaluation, online analytics, predictive analytics Outcome > output, Impact analysis, data-
informed decision-making
Concerns Privacy & Security, Annual costs, Staff skills gap, Competition for
leisure time
Policies, Transparency, Opt-in, Shared
services, Training, Customer experience
Future Trends VR, AR, Photogrammetry, IoT, AI, Image Recognition, Natural
Language Processing, Linked Open Data
Tracking trends via nmc.org, mcn.edu,
museumsandtheweb.com
Major Digital Technology Trends – Let’s Discuss
4
Audience-first:
Big Data
Participation
Personalization
Omnichannel
5
Virtuous Big Data Cycle
Data Opt in Personalized
Communications
Actions
6
Virtuous Big Data Cycle:
Allegiance
Data Opt in Personalized
Communications
Actions
Allegiance
7
Virtuous Big Data Cycle:
Active Loyalty
Data Opt in Personalized
Communications
Actions
Allegiance
Philanthropy
Participation
Brand Advocacy
8
9
Not All CRM Systems are Created Equal
Vendor claims
Expectations
Capabilities
Flexibility
Integration
Scalability
Cost
10
Source: Cisco Customer Experience Research, Retail Shopping Results, Global Data (2013) Available http://www.cisco.com/en/US/solutions/collateral/ns1168/ccer_retail_global.pdf
Show me you know me
11
Segmentation
Groups
Targeting
Groups
Personalization
Individuals
12
Source: http://www.thesealeys.co.uk/
Platform Integration Leads to Omnichannel Experience
13
Content
Storytelling
Content layering
Context-triggered delivery
14
15
16
17
To remain viable, museums must rethink not only what types of knowledge they
create, but how/with whom they create it, and finally how they communicate it.
Scholarship is the foundation of our work. Start there.
Everyone likes an underdog. Don’t do just the highlights.
Level with the visitor. Speak to universal experiences.
Good stories trade on the visitor’s empathy
• Who are your characters?
• What is the situation?
• What decisions did they make?
• What were the stakes?
Choosing stories – Which ones? Why those?
If you do nothing else, get rid of the passive voice.
The passive voice denies people of their agency – and sounds like we’re hedging.
The active voice shifts the focus to people doing stuff.
Not like this guy
DH
Strategy: Name the effort, assign the team
AB
Writing Workshops
Professional writing consultation from Kris Wetterlund,
helped inform:
http://www.museum-ed.org/a-guide-to-interpretive-writing-about-art-for-museum-educators/
23
Context-triggered delivery
Based on content consumption
Recommender engine
Based on location, movement, duration
Beacons, Wifi, GPS
Source: http://1u88jj3r4db2x4txp44yqfj1.wpengine.netdna-cdn.com/wp-content/uploads/2015/05/Taboola.png Source: http://image.slidesharecdn.com/ibeaconpresentationslideshare3-140727230420-
phpapp02/95/stories-asunder-tales-for-the-internet-of-things-11-638.jpg?cb=1425383403
24
Leadership
Lean
Agile
Open
Radical
25
VUCA – Museum Examples
Volatility – Endowment funds hit by recession
Uncertainty – “Treasures of King Tut” suddenly coming to town
Complexity – Explaining attendance changes, too many variables
Ambiguity – Shifting tactics that are not aligned with strategy
26
VUCA prime – Leader’s Response
Vision – purpose is greater than a perfect plan
Understanding – listen so that you can respond
Clarity– see through the fog, respond to what matters
Agility – communicate and change quickly
Adapted from https://growthandprofit.me/2013/07/04/how-to-manage-volatility-uncertainty-complexity-and-ambiguity-part-2/
27
Adapted from: http://changingminds.org/disciplines/leadership/articles/manager_leader.htm
28
Adapted from: http://changingminds.org/disciplines/leadership/articles/manager_leader.htm
29
Background image source:http://www.aisquared.com/wp-content/uploads/2014/05/libraries.jpg
30
Image source: http://hqworld.net/gallery/data/media/40/black_and_white_study_of_a_spiral_staircase.jpg
Agile Methodology • Active user involvement
• All stakeholders collaborate & cooperate
• The Team is empowered to make decisions
• Requirements are lightweight and visual
• Start small, iterate incrementally
• Deliver frequently
• Complete a feature before moving to the next
• Apply the 80/20 rule
Adapted from: http://www.allaboutagile.com/what-is-agile-10-key-principles/#sthash.5DgaON2g.dpuf
31
• Don't wait for a leader to assign work - greater sense of ownership and commitment
• Manage their own work as a group
• Benefit from mentoring and coaching, but not from command & control
• Communicate most with each other - and commitments are to project teams (not management)
• Improve their own skills and suggest innovative ideas & improvements
• Normally become high-performing, measure greater job satisfaction
Adapted from: https://scrumalliance.org/community/articles/2013/january/self-organizing-teams-what-and-how
Principles of self-organizing teams
32
Radical Transparency
Definition:
Use of abundant networked information to access
previously confidential organizational process or
outcome data (adapted from https://en.wikipedia.org/wiki/Radical_transparency)
M.C. ESCHER (Dutch, 1898-1972), Hand
with Reflecting Sphere, 1935, lithograph 12
Courtesy of The Walker Collection
“… the idea of everyone knowing everything, could actually be a
major driver of increased organizational performance … the
biggest reason companies fail is because people lose focus and
get off track”.
- Ryan Smith and Golnaz Tabibnia Adapted from: https://hbr.org/2012/10/why-radical-transparency-is-good-business/
(emphasis is mine)
Radical Leadership: The Servant Leader Model
Adapted from: https://en.wikipedia.org/wiki/Servant_leadership
• shares power
• puts others first
• mentors & supports
• gives credit
Image source: http://www.fratrem.com/wp-content/uploads/2014/01/merlin-robertgreenleaf.jpg
Effective Leadership Lean approach Agile methods Radical leadership Open organization
35
Workforce
Flatter org structure
Innovative hiring
Work-life balance
Disciplined collaboration
36 Source: http://www.steinarhalvorsen.no/wp-content/uploads/2013/04/0260230703001.png
37
Small World Networks: Evolution of Org Structures in Connected Systems
38
Cool Blue
Do a select few
Seek funding & partners
(We wish we could do them all) Risk: Too many at once
(saying yes to everything)
Red Flag
Do only if necessary
Stop! (or proceed with extreme caution)
(We wish we could have none) Risk: Bogs down & exhausts resources
Green Light
Do these fast
Make a prioritized list, get moving
(We wish there were fewer) Risk: Resources pulled away from Cool Blue
Gray Fog
Do only if there are resources
“Busy work” or dreamy distractions
(We wish we had more time) Risk: People fall into it , esp. in times of stress
High
High (Hard)
Low
Low (Easy)
Importance,
Via STRATEGY
Difficulty,
via practical
REALITY
Decision-Making
39
Hire character.
Train skill.
Recommended:
40
Work-life balance – not a simple formula
Source: http://www.adviseamerica.com/wp-content/uploads/2013/09/Statistics-of-Work-Life-Increasing-Productivity.jpg
41
42
Technology
Cloud v. On-premise hardware
Mobile-first
Open source v. commercial software
Content management
43
Source: https://res.cloudinary.com/hy4kyit2a/image/upload/v1454989114/doc/trailhead/images/salesforce_advantage_cloud_premise.png
44
Source: http://www.hrmssolutions.com/wp-content/uploads/2014/05/HRMS-PlanningGuide-CloudOnPremise-table.jpg
45 Source: http://metamonks.com/wp-content/uploads/responsive-vs-mobile-first-webdesign-022-1024x689.png
Open Source Software
• “Free” download
• No company
• Community support
• Can be modified
• Susceptible to security issues
• Requires technical support
Commercial Software
• License fee
• Maintenance fee
• Company support
• Often can not be modified
• May require less tech support
Open Source Software
• “Free” download
• No company
• Community support
• Can be modified
• Susceptible to security issues
• Requires technical support
Commercial Software
• License fee
• Maintenance fee
• Company support
• Often can not be modified
• May require less tech support
Build
• Unique, special requirements
• Consortium model – share
• Staff properly
Buy
• Standard toolsets
• Commodity software
• Best-fit cloud-based services
• Negotiate pricing
Art Objects
(TMS)
Digital Media
Assets
(DAMs)
Website
(CMS) Blogs
MobileWeb
Print (floorplans,
brochures, etc.)
Pubs (magazines,
Catalogs, books)
Press (PR, marketing,
news, etc.)
Documents (reports, plans,
grant apps, policies) Archive
(library, paper files)
e.g., Social
Media Content
Created: Digital
Stored: Analog
Created: Analog
Stored: Analog
Created: Digital
Stored: Digital
Goal: Integrate/share all content
using open APIs and/or web services
Goal: Store in digital format, with
appropriate access permissions in
metadata Goal: Digitize as needed (no mass-
digitization project); store digital versions
in ECM
ePubs
Digital Art-
Time-based media
Enterprise Content Production, Museum-style
Other
©Douglas Hegley 2015
Content
- Object records/metadata
- Constituent records
Potential Content Types
- Maps, charts, diagrams
- LI content
- D& E content (e.g., Verso components
- Etc.
Content Types
- Still images
- Video
- Audio
DAMs
(Open Source)
Enterprise Content Management Ecosystem
Web CMS
DAMs
(Commercial)
Collections Data (CIS)
MetaMia – Search & Retrieval tool
Index & access
Search/Retrieve
Result set
Filters/Facets
Access: Internal
API
API
API
API File Shares
(Not in scope)
Potential needs
- Hot folders for auto-ingest
NEW
NEW
NEW
NEW
Funding for the Mia ECM project provided by: ©Douglas Hegley 2015
50
Queries across:
1. CIS
2. DAMs1
3. DAMs2
4. Web CMS
51
Impact
Formal evaluation
Online analytics
Predictive analytics
52
Evaluation – what is the impact of digital?
53
High-level summary
Time
People who used technology spent more time in the galleries than
those who did not use the technology
even after subtracting the time spent using the technology
Focus
The use of technology does not detract from visitor focus on the art
Visitors described their visit as almost exclusively about the art
(and notably not about the technology)
Stories were recalled up to six weeks post-visit
Use
Visitors used technology in the galleries
They spent a significant amount of time
They read aloud and discussed with each other
54
Analytics: Real-time tracking, sophisticated math – Note: staffing implications (skills)
55
Predictive analytics
• Extracting information from existing data
• To determine patterns
• Apply patterns to predict future trends
• Forecasts, with degree of uncertainty
• Complex math, at times not “humanly discernible”
a.k.a. Random Forest (Brieman & Cutler 2006)
What’s Even Creepier Than Target Determining That You Are Pregnant? (Source: slate.com)
56
Concerns Privacy & Security (of course)
Source: https://media.licdn.com/mpr/mpr/p/4/005/09d/2be/0ac95a3.jpg
57
Concerns Privacy & Security (of course)
Annual cost of technology investments
Wasn’t this supposed to happen?
Source: http://ichef.bbci.co.uk/news/624/media/images/78913000/jpg/_78913431_map1.jpg
58
Concerns Privacy & Security (of course)
Annual cost of technology investments
Staff skills gap
Source: http://fm.cnbc.com/applications/cnbc.com/resources/files/2013/09/06/skills-gap-in-the-US.gif
59
Concerns Privacy & Security (of course)
Annual costs of technology investments
Staff skills gap
Competition for leisure time
Competition is Fierce (and it’s not us versus us)
61
Future Trends
Virtual Reality and Augmented Reality (VR & AR)
Photogrammetry
Internet of Things (IoT)
Artificial Intelligent (AI)
Image Recognition
Natural Language Processing
Linked Open Data
62
Virtual Reality and Augmented Reality (VR & AR)
Source: https://upload.wikimedia.org/wikipedia/en/d/d2/Adapted_milgrams_VR-AR_continuum.png
63
Source: http://lanmarservices.com/wp-content/uploads/2014/11/Photogrammertry.jpg
64
Internet of Things (IoT) … certainly lots of hype
Source: http://www.celent.com/system/files/iot.gif
65
Artificial Intelligent (AI) Image Recognition
Natural Language Processing
Real-time language translation
Content analysis
66
Source:
http://image.slidesharecdn.com/virtuosoodbcli
nkeddataprimer-msaccess-120510190041-
phpapp02/95/exploiting-linked-open-data-via-
microsoft-access-3-728.jpg?cb=1337078459
Goal Big Data in service to the Mission
artsmia.org
Thank you
Douglas Hegley
@dhegley
http://www.slideshare.net/dhegley