7th International Conference on Innovation & Knowledge Management, Bangkok

7th International Conference on Innovation & Knowledge Management, Bangkok

by Madanmohan Rao http://twitter.com/MadanRao
Editor, The KM Chronicles http://bit.ly/TU12l
Bangkok; Oct 9-10, 2014

Logging in now from the 7th International Conference on #Innovation & Knowledge Management, #Bangkok! (IKMAP 2014)

I. Dr. Mathana Santiwat, President of Bangkok University welcomes the delegates from Thailand, Hong Kong, Japan, India, France, Kenya, Australia, USA!
KM and innovation management are key for competitive advantage for companies and countries
Organisations and universities must be catalysts for knowledge and innovation for success
Cross-cultural platforms help exchange ideas and methods for innovation between Asia and the West

II. Prof. Rongbin Lee, Director of Knowledge Management and Innovation Research Centre, The Hong Kong Polytechnic University
“I” stands for international, for innovation, for iPad/iPhone and interactivity!

III. Dr. Vincent Ribiere, Managing Director and Co-Founder, The Institute for Knowledge and Innovation South-East Asia, Bangkok University
“I” is also for informal!
Need a good mix of practitioner and academic perspectives in innovation and KM, bridging theory and practice
Institute for Knowledge and Innovation, Southeast Asia has co-founded the Global Knowledge Network with IKMS/Singapore; Australia; Hong Kong http://km.techsparks.com
Murphy’s Law strikes as Vincent’s slides appear without images, but he does a great job of encouraging attendees to imagine the contents!

IV. Dr. Alex Bennet, Co-Founder and Principal of the Mountain Quest Institute, USA
“Collaborative Advantage in a Competitive Environment”
Competition has its limits, need to explore cooperative approaches also. Classical management/bureaucracy has to be improved
Soft competition is based on reputation; hard competition is ‘dog eat dog’ (power/ego based)
Alex Bennet, former opera singer, threatens to sing opera to wake up delegates if they are inattentive!
Bennet cites naturalist research which shows that survival is not by the fittest, but by those with cooperation, unity, sympathy
Our brains wire us to learn through social interaction: relationships, networks, stimulating family/friends/colleagues
Types of knowledge: surface (visible, easily understood), shallow (context; social knowledge); deep (domain expertise)
Old paradigm: local idea resonance. New paradigm: global idea resonance (eg. due to social media)
Idea Resonance: 1. Personal relationships 2. Work associates 3. Network connections (you may never have met them!)
Competitive collaboration depends on synergy, agreements, trust, collaborative knowledge
Kapeleris: Innovation increasingly involves cooperation and partnerships between a growing network of individuals and organisations
Levels of cooperation: arm’s length; sharing information; sharing and creating new knowledge; sharing insights
Success factors for collaborative competition: deep engagement, real commitment, tangible incentives
Case Study: Tata-Singapore Airlines collaboration: There is compatibility, competitive collaboration & adversarial competition
Knowledge economy is no longer a zero sum game; there need not be a win/lose scenario. Can we learn and share with all?

V. Dr. Arthur Shelley, Principal of Intelligent Answers and Senior Industry Fellow of RMIT University
“Innovative Education Opens Minds, Creates Knowledge and Drives Innovation”
Traditional education has not encouraged cooperation between students, but that can be changed and made more creative with collaborative models
Interdependencies in knowledge and learning can lead to success when knowledge flows are sychronised
The next generation of knowledge leaders will collaborate more via social curation and value creation
Educators today should teach how to build connections and relationships that enable the flow of knowledge and value
Performance is driven by Knowledge (what, when: knowing, experiencing); Skills (how, where: doing), Abilities (why, who: being, behaviours, attitudes)
Lifelong learning has evolved into lifestyle learning (blended into the way people live/work/play)
Evolution of learning: What’s going on -> So what -> Now what
Ask questions in the following order: why – value; who – people; what – process; how – tools
Interactive social learning is driven by a challenge, focus, socialisation, engagement, adaptations, design thinking

V. Puvanart Keoplang: Micro Knowledge Cluster: Competitive Capability Development (CCD) in Action Through KM System In Thailand
ASEAN is creating Economic Community in 2015 (AEC: 10 countries, single market, competitive region)
Thai cluster: characteristics: love people, love motherland, love to do, love to share. Clusters: batik, native woven fabrics, orchid farming.
Social media widely used in Thailand after flood crisis, political upheaval. Used by clusters to share practical knowledge about quality, techniques, new products

VI. Law Bing Lam: Application of KM in Garment Industries of Hong Kong
KM is not just for consultancy and hi-tech firms, but also for labour-intensive industries. Knowledge transfer – one-to-one/few
HK garment industry – management waves: productivity, quality, quick response (JTI), communication (EDI, IT), KM/innovation
Garment industry has largely tacit production knowledge (patterns, printing, embroidery). Transfer to explicit via knowledge libraries (eg. quality manuals, work aids).
Personalisation – via video clips. Ad hoc problem solving groups (offline, online)
Impacts: shorten lead time, quick resolution of technical problems, better quality
Tech Centre set up for KM also capitalises excess IT resources.
Challenges: increasing usage of knowledge libraries, communication barriers, overcoming trust, cultural differences (China, LatAm, Sri Lanka), lack of team work across boundaries
Recommendations: More direct contact, standardisation of terms, new tech tools, better team structuring; empathy: “put yourself in others’ shoes”
Qs: How to capture knowledge of retired staff? How can HK garment industry compete with other regions of the world?

VII. Patrick Rondé: Internal Structures and External Connectedness: Towards a Typology of French Clusters
How do clusters structure themselves, learn internally/externally, improve learning capacity and enhance their performance?
Research questions: Does the complexity and ownership structure of a cluster affect its openness?
France has over 71 clusters in areas like biotech, automotive and wine! French universities have partnered with Chinese universities on wine growing! (Work = Fun!)
(English spoken with a French accent is *the* best! :- )
Cluster differences: number/percentage of foreign MNCs, funding (source/amount), influence (global, regional; central peripheral), size
Clusters can adopt collaborative behaviours through several networking roles

VIII. Dr. Usama Fayyad, Managing Director and Chief Data Officer of Barclays Bank
“BigData, AllData, Old Data: Predictive Analytics in a Changing Data Landscape” (@UsamaF)
What matters: analytics throughout the organisation & ecosystem;
Data scientist is the highest paid position in computer science and IT these days
Data scientists conduct ‘data expeditions’ to explore messy data; discovery and learning on the spot
4 Vs of Big Data: volume, velocity, variety, value
Classic data (eg. relational databases) explodes into Big Data when you add un/structured data via social media such as LinkedIn, Facebook, blogs, etc. in analysing user profiles (social graphs)
Map-reduce – popularised by Google, eg. frequent indexing of a copy of the full Web
Big Data applications and uses: security/forensics, ad analytics, warehouse analytics
Hadoop reduces cost of data storage for enterprises. Data warehouses cost $100K per terabyte per year; $2.5K with Hadoop
Second biggest driver of Hadoop: Extract Transfer Load (ETL).
Value of #BigData: understanding content, context, community sentiment, customer intent
Startup NetSeer senses overall sentiment of an article, matches it to searcher’s intent
Knowledge management is not showing car purchase ads to those who search on ‘automobile’ and have already bought a car
RapidMiner has open source tools for advanced analytics, used by industry and academia
New trend: move the analytics to the data instead of the other way round.
Yahoo correlates email usage with news usage in the same session; incremental revenue of $16 million per year
Cars have simplicity on the outside, complexity inside.
Success comes from converting insights into predictive algorithms, eg. web retailers

IX. Dr. Helen Paige, Founder and Director of The Paige Group Australia
“Knowledge Management, Innovation and Restorative Justice”
Knowledge brokers: often forgotten in the KM world but play an important bridging and facilitation role
Paige cites the innovation framework from Innnovator’s DNA (see my book review: http://yourstory.com/2013/01/book-review-the-innovators-dna-mastering-the-five-skills-of-disruptive-innovators/ via @YourStoryCo)
Brokering takes place across passive/active, radical/conservative spectrum. Links poorly connected worlds, has a strong learning component, can change organisational culture
KM and innovation management can lend conceptual expansion to each other, and new practices

X. Dr. Vishnupriya Sengupta, Managing Consultant, PwC India
“From Transactional to Transformational KM: The MAKE recipe for Enterprise Success”
KM bridges the gap between ‘the bazaar and the Cathedral’
“Anyone who has never made a mistake has never tried anything new.”
PwC has a 2016 Global Knowledge Vision: Networks (‘Spark’ – mobile compliant), Content, Transformation of Knowledge Services
Four principles: Put yourself in others’ shoes (clients), Share/Collaborate, Invest in Relationships, Focus on Value Addition
Many KM initiatives focus on ‘push’ but not enough on ‘pull’ (‘what’s in it for me’)
KM = discipline + way of work + competitive advantage
Global MAKE 2013 winners: Samsung, McKinsey, Toyota, Schlumbeger, PwC, Apple, Google, Accenture, ConocoPhilips, Deloitte
Spark blends elements of social media such as Facebook, Twitter, blogging for enterprise work
Many offices of PwC are migrating from legacy Intranet to Spark, and are seeing benefits already
Spark uses: answering questions quickly, locating expertise, more teams with collaboration, better leadership programs, connection with far-flung events. Video: lots of good testimonials
No more operation in isolation, no more leadership working in ivory towers; 80% reduction in document version control
PwC won Global MAKE Award and Intranet Innovation Award
Pulse: PwC news, account deals
PwC has an online research desk with industry reports; turnaround time less than 48 hours for report requests
PwC has a two-day annual knowledge leadership meetings to share best practices
PwC has client account groups where authorised clients can log in to pose questions and get updates
Spark is three years old, more plans ahead. Next steps: consolidation of our databases

XI. Dr. Ricky Tsui, Director of R&D, ARUP
“KM and Corporate Innovation: What’s the relationship?”
ARUP designed award-winning Canton TV Tower in Guangzhou (nickname: Sexy Lady!), and CCTV, HQ, Beijing
ARUP designed new Mumbai Airport, Beijing Aquatics Centre, Marina Bay Sands Resort, Singapore.
ARUP: Established 1946. Covers design + construction. Lessons learned used for its various projects. Stunning photos!
KM used for ARUP University, project reviews, foresight, skills development, lessons learnt. Starts at induction stage with Knowledge Handbook
Other elements of KM @ Arup: Technical Best Practice, Corporate Yellow Pages, Project Database, CoPs
Enterprise social networking tools include Yammer (tagging of solutions, project knowledge harvesting)
All projects have 3 min video intro. “Project Goodies.” Wiki page (eg. Arup Forge). Open discussion forum
Company created – Oasys – self-developed software packaged and sold to design community
Opal: brainstorming app for (i) early stages of new projects (ii) exploring new business ideas
Arup has 400 internally funded R&D projects each year. External research for new products also. Arup University – 60 accredited internal trainers in Hong Kong. Modules: eg. Smart City
Huge focus: increasing creativity. Creative problem solving approaches – training. A VC is hired to train innovative thinking
Design School modules – CSI (Collective Sense-making to Innovation) – get ideas from outside your usual circles
Learning from nature – inspiration from anthills used to design building without airconditioning in Zimbabwe!
Transfer of innovative design/materials – from Cornwall projects to Beijing buildings
Foresight and visioning exercises: how will buildings and cities look in 2050?
Penguin Pool events (named after London Zoo project): idea exchange with design community, get ideas from other industries, see what can cross over
Corporate innovation methods: Trust, Idea exchange, R&D, Learning from others, Understand future needs, Improve employee skills
Emerging frontiers: use of IoT to design smart cities and smart buildings

XII. Dr. Percy Chan, Quality and Global Supply Chain Director, GP Batteries
“KM Initiation and development in a Manufacturing Company”
Challenges in battery industry (primary, rechargeable) – longevity, cost, safety: poisoning, explosions
Healthy KM helps reduce defects, improve quality, enhance brand, improve marketing
KM success comes from harmonic environment: trust, tools, top-down leadership, involvement of retired staff for seminars/discussion, forums/cafes, IC tools
Knowledge retention by experienced staff includes video recordings + manuals (Standard Operating Procedure)
We invite many outside speakers for seminars; employees who attend external seminars must also conduct internal seminars with takeaways
Each key process has a knowledge broker who is given resources to update knowledge assets and flows
GP Battery blends KM with its Six Sigma practice. Awards given are Black/Green Belts, etc. based on dollar-savings generated (gifts + cash)

Looking forward to Day Two tomorrow! And now: Dinner Cruise on Chao Praya River :-)

DAY TWO

I. Dr Madanmohan Rao, Editor the KM Chronicles (me!) :-)
“Next Generation Knowledge Management: Inter-Organisational Networks and Innovation Management”
The Knowledge Journey of a society: Existing knowledge (Indigenous knowledge, Organisational knowledge), New knowledge (Innovation management; Entrepreneuership, startups)
The Knowledge Cycle in an organisation: New practices (Creativity, invention), Next practices (Innovation, entrepreneurship), Best practices (Knowledge management, performance excellence)
Knowledge flows: Knowledge spiral (internalisation, externalisation, socialisation, combination), Process maps (serial, near, far, strategic, expert transfer), Types (experiential, narrative, symbolic/abstract), Inter-organisational flows (inputs, consultative, cooperative, collaborative, outsourcing, co-creation)
8C’s of KM/innovation management: Connection, Content, Community, Culture, Capacity, Cooperation, Commerce, Capital
Kinds of ecosystems: (1) KM associations/networks (2) company centric (3) government centric
Innovation: Idea generation and brainstorming; Networking with innovators, partners; Co-creation: partners, customers; Engagement with startups and entrepreneurs; Learning from failures; Moving on to new products and services
Ten Types of Innovation: Configuration: (1) profit model (2) network (3) structure (4) process. Offering: (5) product (6) product system or platform. Experience: (7) service (8) channel (9) brand (10) customer engagement
How large companies engage with startups:
Special interest groups (eg. IoT SIG)
Meetups (eg. SAP HANA; AWS)
Startup networks (MobileMonday, Startup Weekend)
Entrepreneurship networks (eg. TiE)
Hackathons (eg. Nokia, World Bank)
Incubators, accelerators (eg. NUS, IIT-Bombay)
Investment (eg. Infosys)
Corporate venture capital (eg. Intel, Qualcomm)
Acquisition (eg. Cisco, Google, Facebook)
Objectives: idea validation, idea generation, new features, new products, new patents/IP, new company (people, markets, culture)
Trend 1: Social Media and KM (i) Knowledge maps: Social network analysis, visualisation tools (ii) Knowledge session formats: Hybrid online + offline, internal + external (iii) Knowledge extraction: Narratives (blogs, microblogs), Webcasts (‘WeTube’)
Trend 2: Maturity frameworks in KM and innovation
Trend 3: Personal KM – creativity, collaboration. Capturing an idea, a relationship, a conversation (Steve Barth)
RT Arthur Shelley @Metaphorage
Terrific overview of the interdependencies of the many factors impacting knowledge flows inside & outside orgs
Insights on the social nature of #KM can be found in Indigenous proverbs. Knowledge sharing always been in all cultures
@MadanRao wooing the participants at #IKMAP about the social nature of knowledge & insights from indigenous knowledge
RT @louise1876 #IKMAP flows of knowledge @ikms_singapore @MadanRao

II. Prof. Chitoshi Koga, Professor of Doshisha University
“Intellectual Capital Research in Japan: Review and Future agenda”
Prof. Koga shares Japan’s intellectual asset mapping, reporting and communication strategies at the country, region, prefecture levels
Agencies involved: Ministry of Economy, Trade and Industry (METI), Patent Office, SME Organisations, Regional Innovation Organisations
Findings: (i) Larger firms have better access to IC resources than SMEs (ii) Context is more important than information
Japan has strong B2B relational capital. “Shared prosperity of business partners and employees” is a strong ethic
Return on Assets (RoA): “Time is money” – quick responses to customer needs saves time, enhances brand
Next IKMAP conference will be in Japan!
Dr. Jun Yao, Assistant Professor, Ritsumeikan University, Japan: IC is both an input and output in innovation
There are not more than five musical notes, yet the combinations of these five give rise to more melodies than ever be heard. – Sun Tsu
The Japanese style of KM is strongly influenced by Japanese style of management & culture; limits to scale?
Need to include studies of trust, credibility, sociology, cultural context and management style in KM/IC strategy

III. Paul Sun, Director of Cloud Computing of Industrial Technology Research Institute (ITRI), Taiwan
“Internet, Cloud Computing, Big Data and its applications”
Trend – “Emerging everywhere computing” – each new computing cycle creates 10X installed base of previous cycle
Reinvention of everything (Mary Meeker): reinvention of OS, communication, channels, content, day-to-day activities, money, industry vertical
AliBaba is becoming one of the Top 5 banks of the world!
Computing costs declined 33% annually from 1990-2013, storage (38%), bandwidth (27%)
Only 7% of Internet is tagged and 1% analysed
Case study: video surveillance as a service (VSaaS)
Generation 1 video surveillance: less than 1K surveillance cameras per site. 2: Less than 10K 3. More than 10K, on cloud
UK has one surveillance camera for every 11 people. China has 30M surveillance cameras; 800K in Beijing (2013)
Processing this video surveillance Big Data: rise of intelligent software analytics agents (eg. in Taipei)
Case study: 500 petabytes video surveillance/day generated, mostly automatically analysed. Faster action than “Big Brother”
We are no longer drinking from the data firehose – we are drinking from the data tsunami!
Reinvention of everything + Cloud computing + Big Data = Tech Tsunami!

IV. István Márton Kiss
“Who Tweets About Technology? Investigating the Role of Twitter in the Diffusion of Technological Information”
Twitter properties: short effective diameter, low reciprocity, short but intense bursts, led by a small proportion of users
Case study: Windows8 and MacOS Mountain Lion launch Tweet frequency. Component size, network diameter, path length, degree distribution
Twitter user categories: officials, enthusiasts, news/blogs, business, techies, average users
Analysis: Top 100 central users, matrix of identity groups v/s in-degree and betweenness centralities
Advantages: quick sensing of market sentiment, insights into product rating/usage
Future research: Tweet quality, sentiment analysis, resolution of questions/concerns

V. Paul Hector
“A Tale of Two Cities: Building an Analytic Framework”
Cities matter in the knowledge economy; concentrations of intellectual capital via human, relationship and structural capital
Comparisons (Bangkok, Addis Ababa): quality of life, salary levels, income levels (rise of slums), tolerance, cohesion; sustainable + smart
Knowledge-based development framework for cities (UNESCO): 4 principles – Pluralism, Inclusion, Equity, Openness.
4 building blocks – Knowledge preservation, creation, dissemination, utilisation
Unexpected insights: there are sharply contrasting perspectives on cultural diversity; definitions/roles of human rights are contested
“We are in danger of making our cities places where business goes on but where life, in its real sense, is lost.” – Hubert Humphrey

VI. Prof. Eric Tsui, Associate Director, Knowledge Management and Innovation Research Centre, The Hong Kong Polytechnic University
“Cloud Computing and Big Data for Supporting Knowledge Work, Innovation and Learning”
Books cited: Taming the Unpredictable; The Future of Work, Predictive Analytics, Case Studies in Service Innovation (Ian Miles)
We are being continually distracted and disrupted at work. Different metrics needed to guide our performance. Reflection, social & lifelong learning needed
We are facing not just information overload but innovation overload (eg. new kinds of social media)
Service industry is based on customer experience, dynamic capabilities, co-creation of value. Cloud helps companies scale, deals with spikes.
MTR (HK transportation, property portal) – hybrid cloud solution
Cloud evolution: today – adolescent cloud. Tomorrow – knowledge cloud. M2M, P2P connections
Cloud services – PolyMath (math discussion), Amazon Mechanical Turk, Recaptcha, UPS fleet maintenance; others in astronomy (spotting galaxies)
More accurate data is as important as your algorithm. “Datafication” – treating content as data
Creativity, innovation, agility are key for excellence in the knowledge economy
Eric Tsui is helping launch a HKPolyU MooC on Knowledge and Big Data

VII. Ratvilai Rangsisingpipat: “Impact of Customer Knowledge Collaboration (CKC) In Product Innovation: Case Study of LeKise Lighting”
Good examples of incremental and radical innovation based on customer insights and tech changes in lighting (eg. number of spirals; LCD/LED).
Recommendations: use direct, persistent and interactive research
Voravee Ruengaramrut: Gamification and Innovation Capability in Thai Firms (knowledge sharing, intra-firm coopetition, organisation learning)
Gamification engagement: Game mechanics – elements, rules; Game dynamics – run-time behaviour
Lugkana Worasinchai: “Exploring Potential Benefits of Big Data in Value Generation in Healthcare Applications” – case studies from six hospitals – longitudinal data in hospitals still largely untapped. Challenges – ethical, political, economic
Allan Deacon: “Managing Quality, Knowledge and Innovation for Competitive Advantage”
Hilarious pics of intended/actual products, quality (Titanic – but crew did not have info/skills), pics of TV sets from 1930s onwards,
“You don’t listen with your mouth open!”
Quality movement phases: quality control – assurance – TQM (product + process + company)

IKMAP Conference closed by Prof. WB Lee and Vincent Ribiere; IKMAP 2016 will be hosted in Kobe/Japan in Oct 2016 by Prof. Chitoshi Koga!
Thanks to Vincent and his entire team for the superb event, looking forward to their next event already: Creative Bangkok, Oct 13-17! http://www.creativebangkok.org/

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