How will we know? Investigating the future of knowledge

production, consumption and sharing

By the National Research Council Canada

ICSTI Insights series – February 2015

Knowledge Management

How will we know? Investigating the future of knowledge

production, consumption and sharing

June 25 2014

You are invited to spend time

in the not-so-distant future

Knowledge management practices and initiatives are

challenged by, and evolving through, the increasing

complexity and interconnectedness of the knowledge

domain, and the need for new KM paradigms and tools that

combine and extend the techno- socio-cultural foci of

traditional KM activities.

This document has been prepared as a backgrounder to set

the stage and inspire discussion by addressing the following

question:

What are the major

trends that have the

potential to affect the

future of knowledge

production, consumption

and sharing?

This research explored the interplay between various trends influencing the evolution of knowledge work. As we did, we continuously bumped into a set of tightly meshed contextual factors underlying each of these trends, pointing to the value of relationships in the creation of

knowledge and business value.

These factors highlighted an under-

lying tension between:

• Trust and fear

• Collaboration and competition

• Transparency and control

(privacy/security)

These factors reverberate in various

social, technological, ethical, legal,

economic, political and environmental

fronts and are present both internally

between employees and externally in

relation to partners and competitors.

The following pages highlight five

thematic areas in which the foremost

trends and influences converge:

• The Porous Organization,

(Context - knowledge production)

• The Connected Nomads,

(Tools and processes affecting

future knowledge production

and consumption)

• Interactive Knowledge,

(Knowledge sharing and production)

• Augmented Insights,

(Information analysis and Foresight)

• The Rise of the Living Data,

(Data Management)

You will notice that we are “talking

from the future” within these thematic

areas, with a fluid time horizon ranging

from the very near future (as little as

1-2 years, as with mobile and social

technologies) to 15+ years down the

road (as with artificial intelligence and

automation of knowledge work).

The porous organization

Driven by the benefits of collaboration, organizational

knowledge is unlocked, circulating across organizations,

countries and sectors of society. Innovation is spurred by

encouraging non-specialists to think openly and share ideas

with the specialists capable of translating their visions into

reality. Transient advantages outperform stable competitive

advantage models. Scientific enterprises are transformed

from the primary producers of knowledge to facilitators of

collaborative innovation and managers of collective digital

assets. Trust and relationship management strategies top

the C-Suite agenda.

Intellectual property models redefined

Distributed IP ownership models have

emerged from the dynamic management

of strategic alliances and outsourcing

partnerships, thereby accelerating

knowledge flows and commercialization

processes. Knowledge mobilized through

social relations is valued as an economic

resource, with evolving sets of control

and profitability mechanisms.

Government RTOs are challenged by

financial restrictions and procurement

roadblocks.

Open government, open science, open data

Openness is a widely established working

model in science, government, and data.

After years of experiments, learning

initiatives and the arrival of the millennial

generation in the workplace, models of

open dialogue and stakeholder engage-

ment drive evolution in science and

government. Participative user-centered,

public-private-people partnerships

innovation models such as living labs and

open labs replace tech transfer programs

and drive many R&D initiatives.

Boundaries are vanishing

Distance, frontiers and delays have

vanished - everything is local and

immediate. The push for openness,

the complexity inherent in the scientific

issues of the day, and the global nature

of business are conspiring to blur

institutional boundaries. Knowledge

flows are shifting from top-down to

multi-directional, with information

being shared freely within and between

organizations and the public. Leadership

is expected from everyone.

The connected nomads

Technology is transparent and centered on value and

knowledge creation. Processing power resides in the cloud

and fog, with augmented worker capabilities, facilitated

collaboration and social interaction. With career volatility and

instant team configurations, people are interacting and moving

from multiple organizational and social networks at a rapid

pace. These changes give rise to many new forms of virtual

interactive collaboration as knowledge products are produced

through social media-like tools. With smaller, intuitive, wear-

able and sensor-packed devices, people are immersed in

personalized information feeds, networked everywhere,

in real-time. Virtual currencies and the sharing economy

account for an even greater percent of economic activities.

Social networks and communities

Social technologies used for business

purposes are having an impact on

practice, engagement, and expertise.

They cluster functionality around

sensemaking, unleash creative forces

and foster adaptive working relationships

and group dynamics. Connecting and

sharing of information across organiza-

tional and global boundaries raises the

productivity of knowledge workers by

20-25% through streamlining commu-

nication and collaboration, breaking

down silos and extending the company’s

knowledge and expertise networks.

Mobile technology

Communication is instantaneous at

marginal costs. Advanced wireless

networks offer seamless transition

between office and home mobile

applications (apps) and data services.

Mobile apps improve productivity and

delivery of service by integrating

communication more directly into

distributed knowledge work and

providing continuous interaction with

colleagues and customers. Everyone

and everything is expected to always

be “on” and accessible. Access

permissions, data security, merging

corporate and personal content and the

use of unsanctioned IT services are the

critical parameters of operational

environments.

Virtual workers career fluidity

Global virtual workers are prevalent, with

contractors and collaborators moving

swiftly from one organization to another,

rapidly connecting and accessing the

expertise and knowledge base of

organizations. Developing a shared

language across communities replaces

knowledge capture and transfer issues

as a knowledge management focus.

Employers compete for talent as corpo-

rate values are scrutinized by candidates.

Personal resumes are replaced by web

profiles and social-based rating systems.

Interactive knowledge

Knowledge work has become interactive for more

employees who, without specialized training, engage in self-

serve intelligence gathering and routine analysis through

personalized dashboards. Advanced collaborative analytics

heightens the value of engagement with clients and partners

outside of the organization. Decision making and innovation

processes are being transformed through easier access to

collective knowledge and collaboratively created insights.

Crowdsourcing allows for the influx of new knowledge and

greater connections within and beyond corporate boundaries.

Collaborative analytics and decision making

Intelligence analysis and decision support

are performed through collaborative and

iterative data modelling with clients and

experts. With integration of visualization

and collaboration directly into knowl-

edge work tools, the focus stays on the

analysis, and the work flow and produc-

tivity are no longer interrupted as with

stand-alone collaboration tools (e.g.

chat, email). Participation facilitates

sharing and socializing of findings

and decisions.

Crowdsourced Innovation

Knowledge is widely dispersed and the

suite of expertise needed to bring new

ideas to fruition is rarely housed in a

single organization. The creation of

intelligence and innovation takes a

distributed, participatory approach,

reducing costs and accelerating time to

market for those organizations willing

to crowdsource their innovating.

Knowledge work is increasingly per-

formed via participative models as the

Work shifts from searching for contribu-

tions to synthesizing and building upon

or co-creating outputs within and for

the community.

Plugged-in agile knowledge

Data science moves from the specialist

to a range of employees. Workers make

use of self-serve, agile analytic tools and

expect flexibility and usability from their

dashboards. Analytics is embedded in

transactional systems and data usage is

plugged into day-to-day operations and

decision making, ultimately impacting

financial, organizational and personal

performance.

Augmented insights

The combination of advanced analytics, interactive

visualizations and artificial intelligence autonomously finds

new patterns in complex data and delivers personalized,

prescriptive advice. Scientific discoveries and business

efficiencies are increasingly made through automated

identification of connections in unstructured data, challenging

the role of theory and the human role in interpreting know-

ledge. Human intuition adds value to strategic decisions and

business innovation. Predictive and prescriptive analytics are

incorporated into less than 25% of business analytics projects

but deliver at least 50% of the business value.

Artificial intelligence (AI)

Advances in computational speed,

machine learning, and natural user

interfaces allow computers to aggregate

information faster than the human brain

and interpret and evaluate the results.

Machine learning excels at the complex

analytics used to monitor activities,

understand the root causes of issues as

they arise and accurately forecast future

trends on the horizon. AI increasingly

handles tactical and operational decision

making, freeing knowledge workers and

managers to focus on the strategic.

Prescriptive analytics

A rise in prescriptive analytics will

go beyond generating foresight and

anticipating the future (predictive

analytics), to define a preferred course

of action for reaching future goals.

Sophisticated analytic tools augment

knowledge workers’ skills, supporting

tasks that rely on complex analyses,

subtle human judgments and creative

problem solving.

Knowledge-work automation

Advances in AI will make it possible

to automate many knowledge workers’

tasks that have long been regarded as

impossible or impractical for machines to

perform. The greatest benefits are found

in applying knowledge work automation

to areas that boost employee productiv-

ity, creativity and allow for bottom up

innovation. Managers have learned to

let the organization run instead of con-

trolling it, and have spent the last

decades transitioning people and

departments affected by the complete

replacement of knowledge workers

by machines.

The rise of the living data

Data no longer lives in static repositories. Data has been

restructured into dynamic ecosystems with open access and

open standards to ensure accessibility and interoperability

on any platform, by anyone. Data is managed using

ontologic and semantic structures, making search and

analysis more meaningful and more effective for non-

specialists. Datasets, both big and small are routinely mined

to produce meaningful, actionable analysis and insight.

Information governance

With records being born digitally and an

ongoing redefining of what constitutes

a ‘record’, records management shifts to

information governance, focussing on

proactively managing data and informa-

tion throughout their lifecycles. Works-

in-progress, structured, unstructured and

semi-structured information all require

governance including protection from

deletion, unauthorized use, and pre-

mature disclosure. Open standards are

implemented across the board to address

preservation and interoperability issues.

Data ecosystems

As data expands in volume, variety and

velocity, data curation is moving to the

forefront, with machine readability and

findability becoming critical concerns

for records/data managers. Traditional

databases and information sources are

replaced by living data ecosystems.

Automated ontologies, semantic web

and inference technologies enhance

search relevance, real-time analytics and

data visualisation by building connections

between information/data sources into

the structure of each system.

Data ownership and access

Data access and ownership is democra-

tized as usage restrictions are minimized

for both published research and their

associated data sets. A change in corpo-

rate and scientific culture is underway

to adapt to the ideals of open knowl-

edge sharing. Competitive edge and

value creation is driven by organizational

capacities to identify, merge, analyse and

integrate findings from a multiplicity of

data sources.

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