Asset management has always involved data-intensive business models, yet today's practitioners are confronted with a deluge of new information arriving in a variety of different formats.
Aligning Information Insights with the Speed of BusinessCognizant
Here is a guide to the technologies, processes and organizational alignment needed to help organizations ensure the viability of information used to facilitate insights in today's accelerated business climate.
The third edition of the BoardMatters Quarterly explores how big data and analytics emerge as game-changers for business. This edition also explores how we can tackle corruption, boosting internal control mechanisms.
Asset management has always involved data-intensive business models, yet today's practitioners are confronted with a deluge of new information arriving in a variety of different formats.
Aligning Information Insights with the Speed of BusinessCognizant
Here is a guide to the technologies, processes and organizational alignment needed to help organizations ensure the viability of information used to facilitate insights in today's accelerated business climate.
The third edition of the BoardMatters Quarterly explores how big data and analytics emerge as game-changers for business. This edition also explores how we can tackle corruption, boosting internal control mechanisms.
Data Governance, the foundation for building a succesful data managementTentive Solutions
This Whitepaper clearly explains how the Data Governance function plays a key role and which factors are of great importance in successful data management. Also available in Dutch.
Enterprise Information Management: Strategy, Best Practices & Technologies on...FindWhitePapers
Authored by Frank Dravis, Baseline Consulting, this paper discusses: (1) EIM strategy development and (2) enabling information management technology. Understanding these two areas is crucial to starting, planning and executing an EIM initiative.
Cracking the Data Conundrum: How Successful Companies Make #BigData OperationalSubrahmanyam KVJ
There is little arguing the benefits and disruptive potential of Big Data. However, many organizations have not fully embedded Big Data in their operations. In fact, our research shows that only 13% have achieved full-scale production for their Big Data implementations. The most troubling development is that most organizations are failing to benefit from their investments. Only 27% of respondents described their Big Data initiatives as “successful” and only 8% described them as “very successful”.
So, how can organizations make Big Data operational? There are many factors that go into the making of a successful Big Data implementation. However, the single biggest factor that we observed in our research was that organizations that have a strong operating model stood apart. This operating model has multiple distinct elements, which include, among others, a well-defined organizational structure, systematic implementation plan, and strong leadership support. For instance, success rates for organizations with an analytics business unit are nearly 2.5 times those that have ad-hoc, isolated teams. The report highlights the key factors for successful Big Data implementations.
The Economist Intelligence Unit surveyed over 600 business leaders worldwide and across different industry sectors about the use of Big Data in their organizations.
The research confirms a growing appetite for data and data-driven decisions and those who harness these correctly stay ahead of the game. The report provides insight on their use of Big Data today and in the future, and highlights the advantages seen and the specific challenges Big Data has on decision making for business leaders.
Key findings:
75% of respondents believe their organizations to be data-driven
9 out of 10 say decisions made in the past 3 years would have been better if they’d had all the relevant information
42% say that unstructured content is too difficult to interpret
85% say the issue is not about volume but the ability to analyze and act on the data in real time
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
“ help.mbaassignments@gmail.com ”
or
Call us at : 08263069601
(Prefer mailing. Call in emergency )
Introducing a new approach for managing information in the digital economyMark Albala
The digital economy requires a new approach for managing information. This series details this new approach. There are eight components to the series, including this highlight.
Originally presented at WordPress Developer night in Bangkok.
We explain to freelance developers and graphic designers how to find clients and key things to customer satisfaction and gain repeat business.
Data Governance, the foundation for building a succesful data managementTentive Solutions
This Whitepaper clearly explains how the Data Governance function plays a key role and which factors are of great importance in successful data management. Also available in Dutch.
Enterprise Information Management: Strategy, Best Practices & Technologies on...FindWhitePapers
Authored by Frank Dravis, Baseline Consulting, this paper discusses: (1) EIM strategy development and (2) enabling information management technology. Understanding these two areas is crucial to starting, planning and executing an EIM initiative.
Cracking the Data Conundrum: How Successful Companies Make #BigData OperationalSubrahmanyam KVJ
There is little arguing the benefits and disruptive potential of Big Data. However, many organizations have not fully embedded Big Data in their operations. In fact, our research shows that only 13% have achieved full-scale production for their Big Data implementations. The most troubling development is that most organizations are failing to benefit from their investments. Only 27% of respondents described their Big Data initiatives as “successful” and only 8% described them as “very successful”.
So, how can organizations make Big Data operational? There are many factors that go into the making of a successful Big Data implementation. However, the single biggest factor that we observed in our research was that organizations that have a strong operating model stood apart. This operating model has multiple distinct elements, which include, among others, a well-defined organizational structure, systematic implementation plan, and strong leadership support. For instance, success rates for organizations with an analytics business unit are nearly 2.5 times those that have ad-hoc, isolated teams. The report highlights the key factors for successful Big Data implementations.
The Economist Intelligence Unit surveyed over 600 business leaders worldwide and across different industry sectors about the use of Big Data in their organizations.
The research confirms a growing appetite for data and data-driven decisions and those who harness these correctly stay ahead of the game. The report provides insight on their use of Big Data today and in the future, and highlights the advantages seen and the specific challenges Big Data has on decision making for business leaders.
Key findings:
75% of respondents believe their organizations to be data-driven
9 out of 10 say decisions made in the past 3 years would have been better if they’d had all the relevant information
42% say that unstructured content is too difficult to interpret
85% say the issue is not about volume but the ability to analyze and act on the data in real time
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
“ help.mbaassignments@gmail.com ”
or
Call us at : 08263069601
(Prefer mailing. Call in emergency )
Introducing a new approach for managing information in the digital economyMark Albala
The digital economy requires a new approach for managing information. This series details this new approach. There are eight components to the series, including this highlight.
Originally presented at WordPress Developer night in Bangkok.
We explain to freelance developers and graphic designers how to find clients and key things to customer satisfaction and gain repeat business.
Organizing to manage information assetsMark Albala
The presentation provides a new approach to managing and measuring the value of an organization's information assets, and gives a brief overview of the roles involved in this new management approach
The first of seven components introduces the new information approach for the information age. The remaining components are available on request by contacting Mark at mark@infosightpartners.com
Managing information in the digital ageMark Albala
This overview provides a new approach for managing information in the digital economy by shifting from management aligned to the sourcing of information to management aligned to the consumption of information by business processes targeted to achieve value propositions
A better approach to managing informationMark Albala
Information is currently managed by how it is sourced and synthesized into analytic frameworks so that it can be analyzed. The analytic frameworks are generalized and decoupled from the processes that consume information, but it is these processes, particularly those with either significant risks or time pressures, that require information be aligned with them so that it can be digested without delay.
The problem is that information is rarely sourced in a way opportune for its consumption. Each process that requires information must gather some from here, some from there and deal with the misalignment of the sources that are used to derive and execute an action plan. No wonder it is difficult for many organizations to use information for much more than business as usual circumstances.
The purpose of this writing is to manage information in such a way so that these non-business as usual and disruptive situations could be identified through some mechanism and the valuation of such information could be assigned so that there is measurable benefit to aligning information to the vehicles that identify such situations, facilitate swift action and ensure intended outcomes.
Slides da palestra da Rivendel no QCon 2015 sobre como construir uma arquitetura escalável com cultura DevOps e uso das melhores práticas de Cloud para ter sucesso no Black Friday
There have been a few times in history which have ushered in a period of great change. We are in the midst of one of them, in which communications and the network has become cheap or free and is influencing changes for the foreseeable future. Some of the changes we are witnessing are the mobilization of the public, a shift in how marketing is performed and the importance of information.
The purpose of this writing is to discuss how information is weaved into this age of disruption and discuss what can be done to thrive in an economy fraught with change for the foreseeable future.
This takes a look at the architectural constructs that are used for building business intelligence systems and how they are used in business processes to improve marketing, better serve customers, and maximize organizational efficiency.
What’s Your Data Strategy· Leandro DalleMule· Thomas H. Daven.docxhelzerpatrina
What’s Your Data Strategy?
· Leandro DalleMule
· Thomas H. Davenport
From the May–June 2017 Issue
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More than ever, the ability to manage torrents of data is critical to a company’s success. But even with the emergence of data-management functions and chief data officers (CDOs), most companies remain badly behind the curve. Cross-industry studies show that on average, less than half of an organization’s structured data is actively used in making decisions—and less than 1% of its unstructured data is analyzed or used at all. More than 70% of employees have access to data they should not, and 80% of analysts’ time is spent simply discovering and preparing data. Data breaches are common, rogue data sets propagate in silos, and companies’ data technology often isn’t up to the demands put on it.
Having a CDO and a data-management function is a start, but neither can be fully effective in the absence of a coherent strategy for organizing, governing, analyzing, and deploying an organization’s information assets. Indeed, without such strategic management many companies struggle to protect and leverage their data—and CDOs’ tenures are often difficult and short (just 2.4 years on average, according to Gartner). In this article we describe a new framework for building a robust data strategy that can be applied across industries and levels of data maturity. The framework draws on our implementation experience at the global insurer AIG (where DalleMule is the CDO) and our study of half a dozen other large companies where its elements have been applied. The strategy enables superior data management and analytics—essential capabilities that support managerial decision making and ultimately enhance financial performance.
The “plumbing” aspects of data management may not be as sexy as the predictive models and colorful dashboards they produce, but they’re vital to high performance. As such, they’re not just the concern of the CIO and the CDO; ensuring smart data management is the responsibility of all C-suite executives, starting with the CEO.
Defense Versus Offense
Our framework addresses two key issues: It helps companies clarify the primary purpose of their data, and it guides them in strategic data management. Unlike other approaches we’ve seen, ours requires companies to make considered trade-offs between “defensive” and “offensive” uses of data and between control and flexibility in its use, as we describe below. Although information on enterprise data management is abundant, much of it is technical and focused on governance, best practices, tools, and the like. Few if any data-management frameworks are as business-focused as ours: It not only promotes the efficient use of data and allocation of resources but also helps companies design their data-management activities to support their overall strategy.
Data defense and offense are diff ...
Enterprise Information Management Strategy - a proven approachSam Thomsett
Access a proven approach to Enterprise Information Management Strategy - providing a framework for Digital Transformation - by a leader in Information Management Consulting - Entity Group
Framework for measuring enterprise agilityTushar Mathur
A thought paper on - what enterprise agility means, why it matters, how enterprises can measure enterprise agility to continue to disrupt and re-invent themselves.
This whitepaper aims to assist Chief Data Officers in promoting a data-driven culture at their
organization, helping them lead the enterprise on a digital transformation journey backed by
analytical insights.
Analytics Isn’t Enough To Create A Data–Driven CultureaNumak & Company
The earned values are perhaps compatible with older technologies. As we believe big data and AI are extensions of analytical capabilities, the most common and most likely to succeed are those related to "advanced analytics and better decisions."
Strategic alignment with bi and ROI AffectFarooq Omar
Information is a key resource that empowers you to keep up or upgrade your market aggressiveness. Insight is in this manner progressively critical to your business. Here we attempt to ponder on the 'Vital' parameters of Intelligence which is the one of the most basic variables of authoritative development and to support in coherence. We have to realize the accompanying utilitarian segments to make an incentive out of it.
Strategic alignment with Bi and ROI AffectFarooq Omar
Information is a key resource that empowers you to keep up or upgrade your market aggressiveness. Insight is in this manner progressively critical to your business. Here we attempt to ponder on the 'Vital' parameters of Intelligence which is the one of the most basic variables of authoritative development and to support in coherence. We have to realize the accompanying utilitarian segments to make an incentive out of it.
189
C H A P T E R 10
Information
Governance and
Information Technology
Functions
Information technology (IT) is a core function impacted by information gover-ynance (IG) efforts. IT departments typically have been charged with keeping the “plumbing” of IT intact—the network, servers, applications, and data—but although
the output of IT is in their custody, they have not been held to account for it; that
is, the information, reports, and databases they generate have long been held to be
owned by users in business units. This has left a gap of responsibility for governing
the information that is being generated and managing it in accordance with legal and
regulatory requirements, standards, and best practices.
Certainly, on the IT side, shared responsibility for IG means the IT department
itself must take a closer look at IT processes and activities with an eye to IG. A
focus on improving IT effi ciency, software development processes, and data quality
will help contribute to the overall IG program effort. IT is an integral piece of the
program.
Debra Logan, vice president and distinguished analyst at Gartner, states:
Information governance is the only way to comply with regulations, both cur-
rent and future, and responsibility for it lies with the CIO and the chief legal
offi cer. When organizations suffer high-profi le data losses, especially involv-
ing violations of the privacy of citizens or consumers, they suffer serious repu-
tational damage and often incur fi nes or other sanctions. IT leaders will have
to take at least part of the blame for these incidents. 1
Gartner predicts that the need to implement IG is so critical that, by 2016, fully
one in fi ve chief information offi cers (CIOs) will be terminated for their inability to
implement IG successfully.
Aaron Zornes, chief research offi cer at the MDM (Master Data Management)
Institute, stated: “While most organizations’ information governance efforts have fo-
cused on IT metrics and mechanics such as duplicate merge/purge rates, they tend to
ignore the industry- and business-metrics orientation that is required to ensure the
economic success of their programs.” 2
190 INFORMATION GOVERNANCE
Four IG best practices in this area can help CIOs and IT leaders to be successful
in delivering business value as a result of IG efforts:
1. Don’t focus on technology, focus on business impact
Technology often enthralls those in IT—to the point of obfuscating the
reason that technologies are leveraged in the fi rst place: to deliver business
benefi t. So IT needs to reorient its language, its vernacular, its very focus
when implementing IG programs. IT needs to become more business savvy,
more businesslike, more focused on delivering business benefi ts that can help
the organization to meet its business goals and achieve its business objectives.
“Business leaders want t.
Data-driven decision-making is an incredible process that helps data science professionals boost their businesses. Explore DDDM in detail and learn how you can master it in 2024
Driving A Data-Centric Culture: The Leadership ChallengePlatfora
Embracing data as a corporate asset—and a source of competitive advantage—is not just a “good idea” that companies should consider. Such adoption will help determine the winners and losers across multiple markets and industries in the future.
In the last couple of years, corporate focus has shifted: first, from investing in the right technology and tools; then to acquiring the right talent and skills; and now to building the right organizational culture that can realize the business value of powerful big-data analytic tools.
Most organizations today are still focused on putting in place the right technology and talent, but others have evolved further and are working toward fostering a data-centric corporate culture.
Similar to The CDO and the Delivery of Enterprise Value (20)
A case for intelligent autonomous ai (iai)Mark Albala
Many argue that 90% or more of the trades on Wall Street are either totally administered without the aid of humans or greatly assist humans in the execution of trades. Although in its infancy, it is easy to envision that this onslaught of the digitization of the marketplace, both in execution and administration has led to the volatility of the marketplace. We are in the infancy of autonomic AI, and the volatility is a condition of AI routines, with no one at the helm, being knee jerk in the reaction to swings in the market caused by other AI routines with no one at the helm. For a historical perspective, in 2014, it was estimated that 75% of trades was originated from automated trade systems. By 2017, JPM estimates were that over 90% of trades were executed algorithmically.
If we further envision, it is easy to assume that the next generation of these AI brokers will understand that they will fall short of maximized profit by following the ebbs and tides of the market caused by other AI brokers, thereby reducing the overall market volatility but also putting traders not armed with these tradebots at a severe disadvantage.
The same logic will hold true to other business functions that succumb to algorithmic execution. The risk will be forever present that knee jerk reactions to every departure from expected outcomes will derail those enabling these algorithms into a whirlwind of turbulence, while those who are smarter in their execution plan will be able to judge such turbulence for what it is, others enabling algorithms to react to every blip.
While today’s autonomic algorithms are smart, they are not intelligent because they are unable to segregate blips from true trends, thereby resulting in knee jerk reactions. This writing will focus on how not to fall into the knee jerker category when implementing autonomic AI.
The long journey toward true data privacyMark Albala
Some recent events have illustrated the long journey we have towards data privacy, all caused by the common recognition issues of information valuation. Two companies that do indeed understand the value of information valuation, apple and Facebook, are at the cusp of a battle precipice that has all to do with the value achieved by Facebook through the monetization of information and Apple’s relentless charge towards protecting the privacy of apple subscribers.
But the fact that Facebook achieved earnings through its actions described in this article and was rewarded by Wall Street illustrates that we have a long road ahead of us, mostly on the cultural and regulatory front, to truly get actions in line with the desires for data privacy. Most importantly, the actions by Facebook have illustrated that while information has value, the regulations governing information have not caught up yet, particularly on defining parental rights for data privacy.
For those of you not aware of the events, Apple and Facebook are currently in a battle over Facebook breaching the app rules governing the harvesting of user data. At the heart of this battle was Facebook’s policy of providing those aged 13 to 35 up to $20 per month plus referral fees to harvest all the data from their mobile devices via a “Facebook Research Virtual Private Network” and use as Facebook saw fit, whether originated from the usage of Facebook or not. Many of those who agreed to receive these moneys were minors, and there has been no provision for parental approval of the use of the Facebook VPN. The Facebook VPN, according to Apple, violated the partner agreement, but again, parental rights never came into the conversation.
This article will define a series of actions that can be anticipated and why the defacto recognition of information value must exist before a realistic approach toward data privacy can become reality.
Analytics, business cycles and disruptionsMark Albala
The digital economy is different. Depending on platforms and a much more malleable set of methods to interact with consumers, an accelerated rate of disruptions compromises the orderly business experience of most market participants. A well-honed analytics program facilitates understanding these accelerated disruptions. With a platform based digital marketplace, obtaining the information necessary to decipher unexpected outcomes and prescribe suitable actions is difficult because the information required Both of these facts are important to analytics. First, platforms. Platform based activity is hard to decipher, not because it is more complex but because the information needed to decipher activity is not contained within your four walls.
Once deciphered, the next challenge facing organizations deciphering unexpected outcomes is a determination of whether the unexpected outcome is truly a disruptive event or simply a phase change in a regularly occurring business cycle. There are significant differences in the suitable reactions to disruptions and business cycle phase changes. Unfortunately, many organizations are ill equipped to discern between these two classes of unexpected business outcomes and consistently find their business plans fall victim to the actions of others within the marketplace.
Luckily, many of the activities of governmental and regulatory bodies are focused on predicting phase changes to the business cycles likely to impact the economic forces within the next fiscal year and describe their economic policies and agendas in publicly available documents and analysis. Understanding where to find these documents and how to use the published to discern between the likely business cycle phase changes and true disruptions as one of the vehicles available within your arsenal of analytics will lessen the occurrence of falling victim in the marketplace by misreading the clues available from unexpected outcomes. This document will address the sources most likely to assist and the actions to be taken to utilize the information attained from these documents.
A process for defining your digital approach to businessMark Albala
This material represents a templated approach specifically constructed to define your approach to digital commerce completed through one or more working sessions.
The business model canvas adapted for the digital economyMark Albala
The digital business model canvas is an adaptation of the business model canvas, a lean approach to defining business models augmented for the realities of digital commerce.
Welcome to the Algorithmic Age and the need for Analytic Accuracy AssuranceMark Albala
We are entering an age where algorithms are the underlying forces that manage interactions with consumers and members of your value chain. These algorithms deliver dynamically optimized content that address the wants, needs and desires of consumers and convert the delivery of the correct content into commercial transactions or referral income opportunities.
Software robots, or the autonomous software agents orchestrated and enabled with artificial intelligence, employ these algorithms to determine a path that optimizes organizational value. In most cases the employed analytics utilize historical data to determine the appropriate trajectories that optimize organizational value. There are times, however, when historical data is a poor predictor of future outcomes. These disruptive times will be commonplace during the foreseeable future. Many solutions that enlist the services of software robots available today do not have some of the critical components to identify and autonomously course correct for these disruptive times.
There are some critical components are often lacking from robotic engines or common business practices and will be described in this writing. These facilities are
A common framework that integrates interactions, the delivery of content, facilitation of referral income and commercial transactions into one integrated common platform-based framework,
Autonomous software capable of identifying when interactions, facilitation of referral income and commercial transactions arrive with unexpected outcomes, and can autonomously course correct,
Software components devised to identify and use the information most resilient to unexpected market forces when prescribing actions to take which are devised to navigate disruption waves,
Autonomous software that can robotically navigate disruption waves when possible and request swift actions from business stewards when appropriate actions to unexpected market cannot be computed,
Sufficiently robust workbench capabilities that allow business stewards to review robotic actions and immerse themselves in redirecting activities when necessary and
Enabling software and enabled teams tasked with the creation and maintenance of robotic software, algorithms, analytics and employed artificial intelligence at the breakneck speed of digital interactions.
There are some major innovations that will stand the chance of changing close to everything that will find their way into the lives of everyone not living under a rock. Some of these are
• major advances in battery technology that will impact close to everything that runs on battery,
• Graphene, a miracle product produced from Carbon that is one molecule thick, stronger than steel, capable of storing electricity and clear. Expect several innovations that will utilize graphene, including a possibility of Graphene disrupting all plastics and possibly aluminum, particularly if the prices sufficiently erode,
• Extended Reality, which is a converged view of the physical and digital landscapes available to the consumer and interacting with consumers in vastly transformed ways,
• Internet of Things (IoT) devices and IoT exchanges, which will allow companies to integrate their physical market presence into the digital processing stream and
• Adaptive Intelligence delivered through autonomous software robots, all interacting with the platforms that collectively represent an organization’s digital identity. Adaptive Intelligence stands the chance of changing close to everything.
All of this is highly disruptive, and during disruptive times analytics lose their accuracy because disruptions represent departures from historical trends. While these will not be the only disruptions that can be expected as, according to Ray Kurzweil and others, we approach a digital singularity, these expected disruptions will represent an opportunity to help shape the future in a way beneficial to the organization, at least if the disruptive times can be deciphered and successfully navigated.
Information's value is enhanced when curated for adaptive intelligenceMark Albala
Much has been written about improving the speed of your digital ecosphere through automation. Organizations that have attempted the automation of their digital ecosphere have discovered that while automation helps the anticipated repetitive tasks, in the configuration used by many organizations it does little to facilitate that which is not anticipated. Yes, automation does free those up who had to previously immerse themselves in the digital transaction stream. The leadership in markets, however, shift to the advantage of those who can read the tea leaves early and act at the blistering speed of the digital economy. The critical timelines require automation, but automation that can deliver status quo responses does not help when expected outcomes are lacking. Adaptive intelligence that utilizes autonomous, robotic software as its orchestration hub is called for, but only if the robotic software is aware of the processes and assumptions used to model the market so that departures from expected outcomes can be identified. With information serving as the lifeblood of the digital economy, leveraging information to its fullest is a prerequisite to survival, and adaptive intelligence is the means to leveraging information.
While there are features and functions not yet matured in many of the robotic process automation solutions, the real underlying roadblock to achieving adaptive intelligence is a lack of mapping the processes and the information consumed by those processes to the robotic software engine. The true leverage to be achieved, the autonomous robots enabling adaptive intelligence must be able to identify departures from expected outcomes and the means to adjust processes to meet the new trajectories present in the marketplace.
This writing will describe the mechanisms you should have in place to orchestrate adaptive intelligence through the facilities of the platforms that interface to your robotic process automation solution(s).
Your digital commerce activities depend on understanding the consumer so that you can share information with the consumer that they will care about. That means harvesting and storing consumer data so that analytics can predict and, in many cases, satisfy the wants, needs and desires of consumers. However, the ability to harvest and store consumer data is contingent on taking reasonable actions to protect that data from being used in ways not disclosed and in ways made possible through data theft (hackers).
92% of consumers have been concerned about the safety of their privacy information being available on line in the vast digital stores of organizations, and their sentiment has been heard by regulators, who have begun to put their foot down. First in Europe, Canada and the Far East, but the spread is contagious. GDPR, the most pervasive of these rules at this time, gives consumers the right to be forgotten from all the digital stores managed by an organization for any reason at all. These organizations have just 72 hours to comply with the request, by law. Stiff penalties have been defined for those incapable or unwilling to comply.
However, the ability to compete on the digital stage is a much larger penalty, and one that organizations should take seriously. Organizations which lose the ability to harvest personal data, either through regulation or due to consumers being unwilling to share with an organization they consider disreputable or incapable when it comes to their personal data, will be at a serious competitive disadvantage in the digital markets because their ability to predict the wants, needs and desires will be seriously marginalized.
Read more on what privacy controls are necessary to participate in the digital economy.
Disruptive outcomes are determined by consumersMark Albala
Digital disruptions are a consequence of the sheer speed of the digital economy and the breakneck speed at which we are navigating the digital economy in route to the autonomous age. Analytics are a core component of activities in the digital economy and will increase their prominence as a core component of the autonomous age. Digital interactions happen without the benefit of human hands. Ultimately, the selection from the various strategies and tactics launched to influence disruptions will be decided by consumers, who through processes of their own devise will internalize content to make their collective choices.
Disruptions occur when innovation, competitive, operational or other activities in the marketplace alter the anticipated outcomes in the marketplace. Disruptions occur in waves. The primary tool available to market participants during disruption waves is to influence the outcome of those waves through persuasive content. However, it is consumers that will ultimately collectively decide the winners and losers during a disrupted market, and their decisions will ultimately be based on content intended on influencing their decisions and their preconceived notions based on their individual views of the marketplace.
Content is the vehicle that market participants wield with intentions to influence consumers, but for content to achieve the intended goals, particularly during times when markets are disrupted, content must be clear and appear to consumers to either support their preconceived notions or appear to be so much of a benefit to consumers that they are willing to forgo any preconceived notions to achieve the intended benefits.
The delivery of this content is just as important as the contents of this content. If consumers cannot find the content or find it at times when they are not likely to give it the attention it deserves, then the intended outcomes are unlikely to be realized. Analytics controlled by self-learning intelligent algorithms are, if available, viable solutions to deliver content at the optimal time and through the optimal media. These algorithms, if effective, must be cognizant of the disruptions and what the potential influences the various actions of market participants will have on the behavior of consumers.
This writing is intended to provide guidelines on how to derive appropriate content to influence disruptions and how to deliver it in ways to influence its outcome in the marketplace.
Introducing the information valuation estimatorMark Albala
In the digital economy, information, properly deployed, is a catalyst for value. It is the information that flows through the platforms that together represent an organization’s digital presence. And it is the pillars of value that represent an organization’s information mantra. Information is nothing less than the lifeblood for converting content to value in the digital economy.
The Information Value Estimator (IVE) is a tool that is used to estimate the effectiveness of information in your organization and derives an attempt to estimate the uplift in revenue that is achievable by improving the management of information as an asset of the organization.
It is absolutely true that analytics is a big part of the equation. However, for the majority of opportunities, particularly when disruptive times prevail, where information can make a big difference is realized when a high degree of autonomous analytics is involved. This autonomy will accelerate the execution of information based actions taken in the digital economy by an organization. A keen understanding of how business processes consume information is required to deploy this level of autonomy. A low level of resistance to putting the faith of the organization into these autonomous analytics is required to optimize value in the digital economy. The means to review, countermand and tune these autonomous analytics is mandatory.
The Information Value Estimator, available upon request, can be used as a self-service tool. Its use is intended to serve as a vehicle to identify initiative opportunities, few of which will be traditional IT opportunities, that will have a measurable impact on the value of information. It is recommended to augment the estimator with a benchmarking of information value to show progress made and refine deficiencies that will impact the ability to wield information in the digital economy.
Cybersecurity is a key ingredient in the digital economyMark Albala
The digital economy is very different. Information is the life blood of the digital economy, and cyber-security attacks are theft of information, sometimes with real financial implications. While too many companies have not revisited their cyber-security arsenal to meet the demands of the digital economy, the regulators have been busy to update the minimally acceptable levels of protection of individuals and their identity in the digital ecosphere. Many companies will be burned by the punitive damages levied by regulators and the reputational damage which impinges upon the ability to conduct digital commerce.
This writing will go through what it means to be cyber-safe in the digital economy and defines a framework that should be used by all organizations to identify the leakages in information either directly leaked by them or syphoned off through imposters misrepresenting the organization. From the regulatory and consumer vantage point, there is not difference, the organizations conducting digital commerce are required to perform the due diligence necessary to provide assurance to consumers that their digital interactions with organizations are secure and safe.
Many companies will appear in the tabloids with massive fines and punishment in the capital markets due to lapses in judgement when it comes to meeting their obligations for cyber-security. Unfortunately, it will take examples made of such companies before the actions necessary to protect the consumer willing to conduct digital commerce is taken seriously. Many of the organizations will not survive the anticipated disruptions.
Deploying and monetizing content in the digital economyMark Albala
The digital economy is very different. The means in reaching and converting consumers into customers is very different in the digital economy. In the digital economy, the delivery of content to customers and prospective customers is accomplished at the convenience of the consumer.
Information personalized to be relevant to the consumer and easily accessed by the consumer through mechanisms chosen by the consumer is critical to digital survival. And devising means to deliver information to the consumer without seeming intrusive is a critical facet of digital survival.
The ability to understand what information will be relevant to the consumer without violating privacy rules. All participants in the digital economy will need to balance the need for analyzing personal identity information against privacy rules and governmental legislation. It is exactly the just in time analytics required to determine what will be pertinent to a consumer based on their content history, their current proximity and a host of other variables is the fuel that will catalyze the monetization of information. It is the regulators watching the obvious transgression of shared personal information, punitive damages and limits to the use of personal information will ensue. This and published occurrences of lapses in protecting entrusted identity information will translate into reputational crises, both of which will force consumers to think twice about sharing their identity information with those wishing to participate in digital commerce. Those hampered by the regulators or incapable of protecting the identity information entrusted to them will suffer the fate of having their ability to know the consumer hampered because of a difficulty to obtain the information required to analyze and personalize content of value to consumers.
The purpose of this writing is to define a framework for obtaining, managing, protecting and monetizing the information fueling the digital economy.
I recently wrote an article on platform intelligence and have come to the realization that intelligence on the platforms that deliver digital products is not the full complement of capabilities required to thrive through in the digital economy. One could excel at managing the platforms used to deliver digital products, but find it difficult to thrive because they are incapable of navigating disruptions, have products that are out of step with the wishes of the marketplace or a host of other reasons. Should they blame their woes on the platforms, they could swap platforms and be no better for these actions.
There are six basic forces, or pillars, which if managed, will greatly improve the ability to thrive in the digital economy. There are facilitators, or the levers to be pulled to influence the enablers, and together they form an ecosystem that together form the pillars of value.
Clearly information is a primary enabler for all the pillars, as it is the conduit for digital products. Content is the information delivered to consumers in the form of reviews, how to videos, advertising and a host of other information devised to inform and influence the opinions of the intended audience. But having content without a means of monetizing the interactions with the intended audience is not sustainable.
The purpose of this writing is to describe a framework for managing an organization’s ability to excel in pillar intelligence. All of the pillars of value are dependent on being skilled in wielding information. Understanding the specific characteristics of information that serve as catalysts of value help thrive in the digital economy.
The digital economy is very different. Products in the digital economy are deployed by offering content, goods and services through a collection of platforms organized in a specific way that makes one digital ecosphere different than every other. And the lifeblood of your digital products is the information and content that defines what a digital transaction will be. To the consumer, the digital experience is the information and content that is navigated for a specific purpose that often eventually leads to a digital transaction.
Content is personalized information specifically devised to influence consumers at specific points of time. A key time to wield this influence is during disruptions, when the market is in a transitional phase. Content can be used as an influencer through the launching of a tipping point to course correct navigation of a disruption wave. Should the content go viral, the influence is magnified (just ask United when they dragged a doctor off his plane).
The pillars to value in the digital economy are dependent on information. Understanding the specific characteristics of information that serve as catalysts of value help thrive in the digital economy.
Introducing thriving with information in the digital economyMark Albala
We are witnessing the shepherding in of the digital age, one where machines and information can do things faster and more accurately than people for select tasks, particularly those that don’t require ingenuity to innovate something that has never previously existed. It is up to those who run organizations to gain a quick appreciation to which tasks benefit from the wisdom, empathy and creativity of the human spirit and which ones are repetitive with minor variations to a theme and best orchestrated through software. It is exactly those organizations that put every task to the whim of a machine that will enjoy an uneasy competitive disadvantage because their finest moments will be those they can be performed by every other business with a machine at the helm for that decision. However, those decisions which are somewhat repetitive and can be taught through software to adjust for the nuances of a decision will be able to react to these activities faster and more accurately than those not benefitting from software, of course without human intuition, empathy and ingenuity. A keen understanding of the processes of an organization, the information supporting that information and how that information potentially makes a difference is at the heart of the discussion of thriving with information in the digital economy.
There are a number of very timely, complex fraught with error tasks that people cringe at performing or tasks which need to be performed at such a blistering pace in the digital age that if they were to wait for people to perform they would either need to be verified carefully for errors or be too late to make a difference in the digital economy. The one thing that is consistent is that the life blood of the digital economy is information delivered at a blistering speed at all hours of the day.
The purpose of this writing is to illuminate some of the changes caused by the digital economy as it pertains to information and help organizations devise a roadmap to their path from the current state to one more applicable for the digital economy.
Introducing thriving with information in the digital economyMark Albala
The attached introduction is a preview of the upcoming book being published by Mark Albala, looking for a publisher to bring this publication to fruition.
Charting your course for surviving disruptive innovationsMark Albala
Historically, businesses could expect the lifespan of their business models to survive the planning horizon of 3 – 5 years and long term strategic planning was something you could review on a quarterly basis and revisit once a year. However, the digital economy has changed all the rules, no longer can you expect the business climate to survive for the planning horizon; typically, digital products are retooled at least twice a year. Moreover, disruptions can come from other sources than innovations, they can be the result of opportunistic and cyber-attacks, the result to your bottom line is the same.
Devising a strategy and first line of defense is mandatory for those who would rather weather the storm of disruption unscathed to the more common alternative of weathering a fire drill with uncertain outcomes. Having an early warning beacon is a central component of early detection of a disruption and corralling the necessary information to inoculate the attack. This writing will go over some of the techniques available for such an endeavor.
Information's role in disruption cycles and the exploitation of tipping pointsMark Albala
“The Tipping Point”, written in 2000 prior to the digital economy, described a means for forging disruptions through the exploitation of information. Having a keen understanding of the information you have at your disposal and a keen awareness of the attempted disruptions through viral social media and other means is critical for survival in the digital economy. This writing will go over what the tipping point is, how information aligns to the tipping point in the digital economy and what organizations must do now to survive disruptive attempts to dethrone their products and services in the digital economy.
Why is cyber security a disruption in the digital economyMark Albala
As we enter the digital economy, companies will quickly realize that the differentiator in the digital economy is information and information being a valuable resource is subject to theft, hacking, phishing and a host of other issues which compromise a company’s ability to participate in the digital economy. Cybersecurity misfires compromise the trust of buyers and partners necessary to participate in the digital economy. It is up to every company to ensure that the information shared with them is protected to the best of their ability and proactively notify persons and organizations who entrust their information necessary to transact business (any personal identity information including but not limited to addresses, credit card information, social security numbers, account information, credit information, medical records, etc.) with any potential compromises which can yield harm to them by that information either being used maliciously or shared with others.
The digital economy is different than other versions of commerce because in the digital economy, information is the lifeblood of digital commerce that passes through the hands of many platforms involved in a digital event. Each of these platforms are an opportunity to wreak havoc on your well-intended but incomplete intents to protect the information contained within the network you control. In the digital economy, it is not only the network you control, but the platforms that touch the personal data entrusted to you as a means of enabling digital commerce, and several techniques have begun to emerge to protect personal information contained within your information domain and the domain of platforms participating in digital commerce.
Because the life blood of the digital economy is information, information hacked in the digital economy is akin to shrinkage in the legacy economy. Both are means to directly attack your bottom line, whether it is redirecting customers elsewhere because they don’t trust your privacy program, ransomware which makes your site or one of your partner platform sites dangerous to use or some other reason which challenges your ability to participate in the digital economy. Shrinking the potential market share because of information safety and security challenges is a disruption, making cyber-security a disruptive activity, particularly if it is not dealt with swiftly.
If your cyber-security program is focused entirely on protecting the information housed in your four walls, you have exposed yourself to problems you will have difficulty in identifying both the source and the entry point of these issues.
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Each strategy and tactic of the organization is
comprised of a number of factors that are
brought together for the explicit purpose of
successfully executing a value proposition.
These factors can be the partners and resources
participating in the strategy and tactic, the
customers, the delivery methods, the cost
structure and other factors. For the purpose of
this paper, we will use the Business Model
Canvas, as described in Value Proposition
Design (Alexander Osterwalder, 2014).
Rivers of information flow through the Business
Model Canvas, and when collaborated among
the actors participating in a specific strategy or
tactic, influence the success or failure of a value
proposition. This influence is the measurable
value of the intangible information asset.
Data in the form of innovations, knowledge,
heard inferences and learned inferences is
rarely used directly. While the value of
information is measurable, it is somewhat more
difficult to directly or indirectly measure the
value of data. Data is the raw material for the
finished goods of information, but just like other
intangible assets, only obtains value through its
usage.
The value of information is enhanced when it is
used in critical situations. For example,
information that helps Apple thwart off the next
great competitor to the iPhone is worth much
more than information used to produce a
standard analysis. Generally, the more critical
situation presented, the shorter the lifespan of
the increased value for information. In the
equity markets, there is high value for
information that is immediate and very little
value for information that is 15 minutes old.
There are a number of core competencies which
an organization must possess in order to be able to
associate the CDO’s activities of influencing the
value proposition processes through the use of
information. Some of these key competencies,
which we will discuss further include:
The CDO Revenue Recognition
Roadmap
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Treating information as an intangible asset of
the organization. Just like organizations which
manage patents or digital assets, a function
specifically devised to manage the information
assets of an organization must be in place.
Understanding the potential role that
information can be used to generate captured,
extended, protected or created value for the
organization. A clear understanding of the
business processes that yield value propositions
and revenue for the organization and the
information that supports that process is
required. The business model canvas has been
chosen as the vehicle to describe the business
processes and the supporting information due
to its simplicity to construct and explain.
Identifying the high value usage of information
and ensure their inclusion in the business
processes. These are commonly the most
disruptive threads in a business model and often
represent mis-executions of the business
processes, fraud or disruptions that require re-
innovation of the business model.
Mitigating the items that constrict the
obtainable value from business processes. The
common items can be:
Lack of trustworthy information (while data
quality is a big piece of this equation, there is
no trustworthy information if the
stakeholders of the business processes do not
believe it to be trustworthy).
An environment where it is difficult to find the
relevant information in time for it to be used
(fostering an environment where all the data
everyone would possibly need is not
necessarily a good thing because such an
environment could obfuscate what is critical
at the moment).
Lack of understanding of the derivation,
lineage or provenance of information.
Lack of attribution applied to the information,
making it difficult to understand the context
of the information supporting the business
processes.
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Possessing a process which measures and
communicates the value and associated
revenue attributed to the CDO activities.
Understanding and fostering the interplay of
the participants (the CDO, CIO, DGC and DAM,
all in the preview of this paper) in the
recognition of revenue attributable to
information (which is transformed from data in
the form of innovations, knowledge, heard
inferences and learned inferences).
There will always be value obtained for
information as it is consumed in the strategies
and tactics of the organization. However, few
organizations are prepared to capitalize on the
highly critical and short-lived opportunities
and risks presented through information. The
CDO serves as the catalyst to ensure the
exploitation of information in these cases. This
is done by:
Ensuring the inclusion of high value usage of
information in the strategies and tactics of the
organization.
Devising a mechanism to measure the
contribution of information to the strategies
and tactics of the organization.
There are several barriers to the successful use
of information in high value circumstances,
described in this paper as the information value
levers. The CDO, in concert with the other
leaders of the information assets of the
organization, ensure that the information value
levers facilitate the optimal use of information in
these high value circumstances. The CDO should
own a scorecard that measures the continued
improvement of the information value levers, as
the improvement of the information value levers
is a key measurement in the effectiveness of the
CDO.
The effectiveness of the CDO is measured using
two key metrics.
The influence by the CDO in the consumption
of information in the strategies and tactics of
The CDO as the Catalyst for Enhancing
the Value of Information
Measuring the Effectiveness of the
CDO
the organization. A means to transcribe this
influence is provided in this paper.
The improvement of the information value
levers. A more comprehensive list of the
information value levers is provided in this
paper.
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Information gains a high percentage of the value
proposition achievable from the strategies and
tactics of the organization. Disruptive use of
information (launching a disruption in the
marketplace or influencing the outcome of a
disruption launched elsewhere) captures a
disproportionate percentage of the value
proposition.
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In the Big Bang Disruption , 12 steps are described in
which a disruption manifests itself to an
organization’s value proposition. The effect of the
disruption is a function on the organization’s ability
to wield information. It is only through the effective
yielding of information that the disruptions can be
successfully identified and then translated to the
necessary changes to processes utilized to yield
organization value. It is only through the proper
managing of the influencers of data and the
effective relationships between the CDO, DAM, DGC
and the CIO that this can be achieved.
The CDO will be accountable for reporting the
incremental value achieved by the use of
information influenced by the CDO and the cost
expended to influence the extraction of information
value.
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Big Bang Disruption, Strategy in the age of Devastating
Innovation, Downes and Nunes, 2014
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Information Value
Value Proposition
Maximum Value
Achieved Value
Major data levers
limiting attainable
value are magnified
in time critical
situations
Effectiveness of
data governance
Information
trustworthiness
Ability to easily
identify appropriate
information
Full attribution
of Information
Information
provenance
Information use
accelerator
effectiveness
Collaboration
effectiveness
Figure 2 | The Value Achievable from Information
Disruptive
Strategic
Tactical
Operational
4. Transcribing the CDO's influence of
enterprise value
In order to transcribe the CDO’s influence of
enterprise value, the mapping of information to
the value propositions of the organization and the
derivation of this consumed information must be
completed. The CDO should be responsible for:
Mapping the information targeted for
consumption in a business model canvas (the
representation of the strategies and tactics of
the organization).
Deriving the data required to have the
necessary information available for
consumption just in time for business events
triggering the use of business model canvases.
Measuring the impediments to ensure just in
time availability of information and timely
execution of the enterprise strategies and
tactics.
An effective CDO will be measured by their ability
to influence the high value usage of information.
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The net profit achieved by the CDO’s activities are
the difference between the value achieved by the
intangible information assets of the organization
and the cost of ensuring the usability of this
information through governance, data quality,
metadata, lineage and other programs which
mitigate the challenges that thwart the use of
information in high profile circumstances.
Some examples of real high profile circumstances:
The valuation risk associated with negative
international press coverage caused by a
manufacturing defect in automotive ignition
switches.
The successful market capture of a large block
of cell phone customers by eliminating their
contractual obligations to obtain device
discounts.
The successful thwarting of an SEC audit and
associated press coverage caused by
undetected trade irregularities not surfaced in
compliance reporting.
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Figure 3 | 12 Steps of the Big Bang Disruption Cycle, Big Bang Disruption, 2014
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— Consult with Visionaries (CDO enabled)
— Separate little bumps from disruptions (big bangs)
— Innovate to determine strategies to thwart
disruptions
— Alter the processes deriving a value proposition
— Be the winner take all in the markets
— Slow the process of disruptors in the
marketplace
— Anticipate Saturation
— Shed assets before they become liabilities
— Abandon value propositions where success is not
viable
— Escape your own black hole
— Transform some value propositions to suppliers
— Return to a new singularity
Disruption
Start
(The singularity)
The Disruption
(The Big Bang)
Returning to
Equilibrium
(The Big Crunch)
Entropy
5. There are several activities all of which will be new
to the organization and should be tracked to
determine if the measurement of information
influence on the processes that derive
organizational value are effective. These new
activities require a coordination of the processes
used to capture, create, extend and protect
organizational value, and the information used to
derive this organizational value and the data
transformed to serve as the consumed
information. There are four organizational roles,
some may exist in today’s organization, including
the Chief Data Officer (CDO), the Data Asset
Manager (DAM), the Data Governance Council
(DGC) and the Chief Information Officer (CIO).
Metrics should be created on the factors that limit
the use of information and the effective
coordination of the CDO, the DAM, the DGC and
the CIO.
Furthermore, the recording of value influenced by
information and the resultant revenue must be
recorded for the entire justification of the
investment made to ensure the optimal use of
information through the efforts of the CDO, DAM,
DGC and CIO. Metrics to measure the revenue
attributed to information usage as a percentage of
organizational revenue should be created. This
Each of these examples require swift use of information to either capitalize on market opportunities or
thwart risks exposed through the successful use of information.
process needs to be followed to measure the
effective participation of the CDO and to record
revenue attributable to the efforts of the CDO.
There are technology, people and process
contributors that influence the valuation of
information. All of them are vehicles that, when
successfully implemented, facilitate the use of
information just in time for the execution of
strategies and tactics of the organization and the
successful identification and capitalization of
opportunities and risks associated with the
strategies and tactics of the organization.
Under certain circumstances, there may be
situations where a disruption has occurred in the
marketplace which is not covered by any of the
business models of the organization. In such
cases, a process for business model innovation,
which is itself one of the information value levers,
is engaged to modify the strategies and tactics of
the organization to fit the new market realities. In
such cases, information may have to be
formulated on the fly to fit the new strategies and
tactics. While such ‘just in time’ transformation
capabilities are rare, these are especially valuable
to the organization when such opportunities and
risks present themselves.
Improving the Information Value Levers
Figure 4 | Data Map a Business Model Canvas
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Business Model Canvas (BMC) Data Map
Protected Value
(Risk Remediation)
Captured Value
(New Relationships)
Extended Value
(Extend
Relationships)
Created Value
(Successfully
Innovate)
BMC
Value Proposition
How Value is Identified
What activities are
triggered to
achieve the value
proposition
Information that
triggers the executed
events
The derivation of this
information
The source data
consumed
6. The Participants in Influencing
Enterprise Value through the use of
Information
There are several participants who have a stake
in influencing the value of information, and
thereby, play a role in the revenue attained by the
Chief Data Officer. These participants are the
CDO, DAM, DGC and CIO. The reporting
relationships for each of the four roles will vary
based on the industry and organization.
The CDO, DAM, DGC and CIO, all play a pivotal
role in effectively influencing the value of
information as an intangible asset consumed in
the strategies and tactics of the organization.
The Business Model Canvas (discussed in this
paper) and the BMC Data Map (also discussed in
this paper) are the vehicles to map the
consumption of value to the value propositions
of the organization as a means to determine
the maximum value achievable through the use
of information.
It is important to note that while the availability
of data is critical to the use of information in the
strategies and tactics of the organization (as
mapped out in the BMC Data Map), data of and
by itself achieves no value for the organization.
Just like the intangible patent assets of an
organization have potential value which is
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achieved by the royalties attained or the use of
the patent to deliver goods and services to a
customer, the intangible data assets of the
organization are consumed in the strategies and
tactics of the organization and achieve value as
mapped in the BMC Data Map.
It is the responsibility of the Chief Data Officer to
identify and record the achieved intangible
information asset valuations accomplished and
the cost of transforming the raw data materials
into finished goods inventory.
It is the responsibility of the data governance
council to identify, prioritize and remediate
impediments that lessen the achievable value
for consumed information, such as its
trustworthiness, full attribution and other data
levers associated with the use of the
information.
It is the responsibility of the CIO to ensure the
execution of the priorities identified by the data
governance council to optimize the achievable
value for information.
And finally it is the responsibility of the data
asset manager to manage the raw data and
finished goods information assets of the
organization.
Figure 5 | Typical Information Value Levers impacting the value of information
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Information and Data Value Influencers
Technology Contributors People Contributors Process Contributors
— Collaboration Aids
— Measurement Aids
— Reference Data
— Attribution / Metadata
— Active Taxonomy
— Information / Context
integration
— Workflow
— Consolidation Aids
— Big Data Management Aids
— Governance Aids
— Infrastructure Aids
— Actionability Aids
— Expired Data Removal Aids
— Information Lifecycle Mgmt.
— Information Transparency Aids
— Operational Data Quality
— MDM Isolation
— Sharable Environment
— Information Attribution
— Non-Expiration Assurance
— JIT Accessible Assurance
— Trustworthy Assurance
— Actionability Aids Effectiveness
— Non-Reliance on Local Data
— Willingness to Share
— Sponsorship
— Readiness
— Orchestration
— Effective CDO optimization of
information used to derive
organizational value
— Effective Data Asset Mgmt
— Effectiveness of identification &
prioritization of material changes to
critical data elements
— Accurate mapping of information to
business model canvas
— Active process to ensure alignment of
information taxonomy and current
organization informational needs
— Process/Organization Fit
— Identification Effectiveness
— Ownership Assignment Effectiveness
— Strategy Derivation Effectiveness
— Collaborative Executing Effectiveness
— Feedback Measurement Effectiveness
— Executed Actions fine tuning
Effectiveness
7. It is the interplay of the CDO, CIO, DGC and DAM that the net incremental revenue achievable from
information for the organization is attainable.
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Chief Data
Officer
Data Asset
Manager
Data
Governance
Council
Chief
Information
Officer
Influence the optimal mix of
information consumed in
creating, extending, capturing
and protecting organizational
value.
Manage the inventory of
the raw materials (data)
and finished goods
inventory (information)
available to the
decisioning processes
Influence the attributes of
data that improve its
identification, usefulness,
trustworthiness and
actionability
Own the processes that
create and acquire data
for the organization and
execute activities
identified by the others
that systematically
improve the value of data
Management of Data and the
synthesis of information
Influence the uses of information and
ensure the availability by mapping to data
In summary, two things that every CDO should consider as critical paths in the years ahead are to
understand and advocate that:
Information should be treated as an intangible asset of the organization.
The CDO is in a position to be the catalyst for enhancing the value of information.
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Figure 6 | The Roles participating in influencing information value