The second in the series of "Rethinking Information Strategies" focuses on shifting from a supply based strategy to a consumption based strategy for the information assets of an organization.
Master Data Management: An Enterprise’s Key Asset to Bring Clean Corporate Ma...garry thomos
Over the last several decades, IT landscapes have proliferated into complex arrays of different systems, applications and technologies. Eventually, this fragmented environment has created significant data problems.
A framework that discusses the various elements of Data Monetization framework that could be leveraged by organizations to improve their Information Management Journey.
Master Data Management: An Enterprise’s Key Asset to Bring Clean Corporate Ma...garry thomos
Over the last several decades, IT landscapes have proliferated into complex arrays of different systems, applications and technologies. Eventually, this fragmented environment has created significant data problems.
A framework that discusses the various elements of Data Monetization framework that could be leveraged by organizations to improve their Information Management Journey.
Don't Let Your Data Get SMACked: Introducing 3-D Data ManagementCognizant
Establishing data accuracy and quality is central to data management, but the SMAC stack - social, mobile, analytics and cloud - both makes it more complex to do so and offers tools for accomplishing the mission. We devised a three-tier "3-D" plan for data management based on integration, data fidelity and data integration.
Strategy how to change Big Data into useful information and win the business/candidacy, and Big Problem into Big Opportunity in the information exposure era.
Slides: Data Monetization — Demonstrating Quantifiable Financial Benefits fro...DATAVERSITY
Data monetization is a cross-functional discipline that draws from best practices in Enterprise Data Management (EDM), technology, legal engineering, and finance to leverage data to increase revenues, reduce costs, and manage risk. EDM programs have generally found it extremely difficult to get senior management buy-in the absence of regulatory pressures or the fear of a data breach. Data monetization is an approach to drive quantifiable business benefits from data and information. This bottom-line driven approach is key to generating business adoption with stakeholders.
This session will review the key aspects of data monetization:
• Introduction to Data Monetization
• Identify Stakeholders
• Build Inventory of Use Cases
• Develop Business Cases
• Execute Initiatives
• Realize Business Benefits
• Legal Engineering and Regulatory Compliance
• Data Marketplace
The data economy is growing globally with more and more organization realizing their core data asset's value. Start here to understand how your company can start your data monetization strategy.
Data Mining: The Top 3 Things You Need to Know to Achieve Business Improvemen...Dr. Cedric Alford
While companies have been using various CRM and automation technologies for many years to capture and retain traditional business data, these existing technologies were not built to handle the massive explosion in data that is occurring today. The shift started nearly 10 years ago with expanding usage of the internet and the introduction of social media. But the pace has accelerated in the past five years following the introduction of smart phones and digital devices such as tablets and GPS devices. The continued rise in these technologies is creating a constant increase in complex data on a daily basis.
The result? Many companies don't know how to get value and insights from the massive amounts of data they have today. Worse yet, many more are uncertain how to leverage this data glut for business advantage tomorrow. In this white paper, we will explore three important things to know about big data and how companies can achieve major business benefits and improvements through effective data mining of their own big data.
Dr. Cedric Alford provides a roadmap for organizations seeking to understand how to make Big Data actionable.
On behalf of SBI Consulting I’ve made a webinar on September 25th about Data Monetization.
In the post covid-19 era, transformation of businesses to govern their data more as an asset will become of huge importance. Becoming more data driven and digital will only increase at an unseen pace.
The essence of this transformation and the emphasis will be on Data Monetization. Monetizing your data assets will be of vital importance if you’d want to remain competitive and survive & thrive in the new normal.
In this webinar “Data Monetization in a post-Covid era”, I cover topics such as:
What does Data Monetization entails
Why Data Monetization is important for your business
How does the post-Covid era impacts this monetization process
What do we mean with Infonomics and Data Debt
The 5 key takeaways to get started with Data Monetization
The outcome? A good understanding of Data Monetization and practical insights to get going immediately!
Big Data Analytics and its Application in E-CommerceUyoyo Edosio
Abstract-This era unlike any, is faced with explosive
growth in the size of data generated/captured. Data
growth has undergone a renaissance, influenced
primarily by ever cheaper computing power and
the ubiquity of the internet. This has led to a
paradigm shift in the E-commerce sector; as data is
no longer seen as the byproduct of their business
activities, but as their biggest asset providing: key
insights to the needs of their customers, predicting
trends in customer’s behavior, democratizing of
advertisement to suits consumers varied taste, as
well as providing a performance metric to assess the
effectiveness in meeting customers’ needs.
This paper presents an overview of the unique
features that differentiate big data from traditional
datasets. In addition, the application of big data
analytics in the E-commerce and the various
technologies that make analytics of consumer data
possible is discussed.
Further this paper will present some case studies of
how leading Ecommerce vendors like Amazon.com,
Walmart Inc, and Adidas apply Big Data analytics in
their business strategies/activities to improve their
competitive advantage. Lastly we identify some
challenges these E-commerce vendors face while
implementing big data analytic
Big Data and Marketing: Data Activation and ManagementConor Duke
Data Management and Activation
Crevan O’Malley – Evangelist, Oracle Marketing Cloud
Modern Marketers rely on data-driven marketing solutions to deliver more personalised customer experiences across every channel—helping attract and retain the ideal customers who become brand advocates. Discover how to aggregate, enrich, and analyze all your customer data on a single data management platform.
Why Marketers need to know about Data
Tara Grehan - Managing Director at Datalytics
Why Marketers need to know about Data
Tara Grehan - Managing Director at Datalytics
Despite starting out as a qualitative researcher, roles and projects frequently brought me back to data. And so I decided to tackle it and have developed some interesting insights into data management along the way.
Having worked in Marketing both agency and client side for fifteen years now in a variety of roles from Market Research and Customer Insights to Change Management, being comfortable with data has made all the difference and this evening I’ll tell you why.
Using Big Data to Grow on a Budget
Michael Waldron - Marketing and Sales Manager at AYLIEN
AYLIEN is an Artificial Intelligence content analysis startup and Mike will be speaking on their growth journey over the past 6 months. With a focus on how they have delivered growth by optimising their budget, focusing on Data Points that matter and what to points to obsess on through the marketing funnel.
Why there are so many problems with streamlining data strategy ? What are the major problems ? How do you solve them ?
Using an approach based on Agile and Lean Concepts to achieve the goal of actionable data & analytics
Why Big Data is the foundation for Digital Transformation ?Koray Sonmezsoy
ClickZ Live Hong Kong 4-6 Aug 2015
http://www.clickzlive.com/hongkong/agenda-day1.php
Digital transformation is top-of-mind for executives across many industries. Often when thinking of digital transformation, marketers are thinking about how to amplify their digital presence through website enhancements, mobile design and social platforms. While those are certainly key tactics in a robust digital strategy, they are initiatives that must be informed by and based on data.
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
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.
Don't Let Your Data Get SMACked: Introducing 3-D Data ManagementCognizant
Establishing data accuracy and quality is central to data management, but the SMAC stack - social, mobile, analytics and cloud - both makes it more complex to do so and offers tools for accomplishing the mission. We devised a three-tier "3-D" plan for data management based on integration, data fidelity and data integration.
Strategy how to change Big Data into useful information and win the business/candidacy, and Big Problem into Big Opportunity in the information exposure era.
Slides: Data Monetization — Demonstrating Quantifiable Financial Benefits fro...DATAVERSITY
Data monetization is a cross-functional discipline that draws from best practices in Enterprise Data Management (EDM), technology, legal engineering, and finance to leverage data to increase revenues, reduce costs, and manage risk. EDM programs have generally found it extremely difficult to get senior management buy-in the absence of regulatory pressures or the fear of a data breach. Data monetization is an approach to drive quantifiable business benefits from data and information. This bottom-line driven approach is key to generating business adoption with stakeholders.
This session will review the key aspects of data monetization:
• Introduction to Data Monetization
• Identify Stakeholders
• Build Inventory of Use Cases
• Develop Business Cases
• Execute Initiatives
• Realize Business Benefits
• Legal Engineering and Regulatory Compliance
• Data Marketplace
The data economy is growing globally with more and more organization realizing their core data asset's value. Start here to understand how your company can start your data monetization strategy.
Data Mining: The Top 3 Things You Need to Know to Achieve Business Improvemen...Dr. Cedric Alford
While companies have been using various CRM and automation technologies for many years to capture and retain traditional business data, these existing technologies were not built to handle the massive explosion in data that is occurring today. The shift started nearly 10 years ago with expanding usage of the internet and the introduction of social media. But the pace has accelerated in the past five years following the introduction of smart phones and digital devices such as tablets and GPS devices. The continued rise in these technologies is creating a constant increase in complex data on a daily basis.
The result? Many companies don't know how to get value and insights from the massive amounts of data they have today. Worse yet, many more are uncertain how to leverage this data glut for business advantage tomorrow. In this white paper, we will explore three important things to know about big data and how companies can achieve major business benefits and improvements through effective data mining of their own big data.
Dr. Cedric Alford provides a roadmap for organizations seeking to understand how to make Big Data actionable.
On behalf of SBI Consulting I’ve made a webinar on September 25th about Data Monetization.
In the post covid-19 era, transformation of businesses to govern their data more as an asset will become of huge importance. Becoming more data driven and digital will only increase at an unseen pace.
The essence of this transformation and the emphasis will be on Data Monetization. Monetizing your data assets will be of vital importance if you’d want to remain competitive and survive & thrive in the new normal.
In this webinar “Data Monetization in a post-Covid era”, I cover topics such as:
What does Data Monetization entails
Why Data Monetization is important for your business
How does the post-Covid era impacts this monetization process
What do we mean with Infonomics and Data Debt
The 5 key takeaways to get started with Data Monetization
The outcome? A good understanding of Data Monetization and practical insights to get going immediately!
Big Data Analytics and its Application in E-CommerceUyoyo Edosio
Abstract-This era unlike any, is faced with explosive
growth in the size of data generated/captured. Data
growth has undergone a renaissance, influenced
primarily by ever cheaper computing power and
the ubiquity of the internet. This has led to a
paradigm shift in the E-commerce sector; as data is
no longer seen as the byproduct of their business
activities, but as their biggest asset providing: key
insights to the needs of their customers, predicting
trends in customer’s behavior, democratizing of
advertisement to suits consumers varied taste, as
well as providing a performance metric to assess the
effectiveness in meeting customers’ needs.
This paper presents an overview of the unique
features that differentiate big data from traditional
datasets. In addition, the application of big data
analytics in the E-commerce and the various
technologies that make analytics of consumer data
possible is discussed.
Further this paper will present some case studies of
how leading Ecommerce vendors like Amazon.com,
Walmart Inc, and Adidas apply Big Data analytics in
their business strategies/activities to improve their
competitive advantage. Lastly we identify some
challenges these E-commerce vendors face while
implementing big data analytic
Big Data and Marketing: Data Activation and ManagementConor Duke
Data Management and Activation
Crevan O’Malley – Evangelist, Oracle Marketing Cloud
Modern Marketers rely on data-driven marketing solutions to deliver more personalised customer experiences across every channel—helping attract and retain the ideal customers who become brand advocates. Discover how to aggregate, enrich, and analyze all your customer data on a single data management platform.
Why Marketers need to know about Data
Tara Grehan - Managing Director at Datalytics
Why Marketers need to know about Data
Tara Grehan - Managing Director at Datalytics
Despite starting out as a qualitative researcher, roles and projects frequently brought me back to data. And so I decided to tackle it and have developed some interesting insights into data management along the way.
Having worked in Marketing both agency and client side for fifteen years now in a variety of roles from Market Research and Customer Insights to Change Management, being comfortable with data has made all the difference and this evening I’ll tell you why.
Using Big Data to Grow on a Budget
Michael Waldron - Marketing and Sales Manager at AYLIEN
AYLIEN is an Artificial Intelligence content analysis startup and Mike will be speaking on their growth journey over the past 6 months. With a focus on how they have delivered growth by optimising their budget, focusing on Data Points that matter and what to points to obsess on through the marketing funnel.
Why there are so many problems with streamlining data strategy ? What are the major problems ? How do you solve them ?
Using an approach based on Agile and Lean Concepts to achieve the goal of actionable data & analytics
Why Big Data is the foundation for Digital Transformation ?Koray Sonmezsoy
ClickZ Live Hong Kong 4-6 Aug 2015
http://www.clickzlive.com/hongkong/agenda-day1.php
Digital transformation is top-of-mind for executives across many industries. Often when thinking of digital transformation, marketers are thinking about how to amplify their digital presence through website enhancements, mobile design and social platforms. While those are certainly key tactics in a robust digital strategy, they are initiatives that must be informed by and based on data.
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
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.
Data analytics can immensely impact and improve a business’s decision-making processes. From better strategies to profits, explore the full scope of analytics.
Data analytics can immensely impact and improve a business’s decision-making processes. From better strategies to profits, explore the full scope of analytics.
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 ...
Data can be your key strategic asset for long-term growth. Just as the "quantified self" builds awareness of progress toward health, your comprehensive data strategy can help you lead your industry.
Data democratization the key to future proofing data culturePolestarsolutions
Learn how to empower your organization with accessible data insights through democratizing your data. This guide offers tips for choosing the right tools and fostering a data-driven culture.
Presentation to introduce information governance. This should be used in conjunction with the paper I published on my website. A full information governance methodology, with research included from the foremost authorities on data governance.
Big Data and Analytics: The New Underpinning for Supply Chain Success? - 17 F...Lora Cecere
Executive Overview
Today data is everywhere: but, nowhere. The world’s per capita capacity to store information has doubled every 40 months since the 1980s; and as of 2012, every day globally, 2.5 exabytes of data are created . As a result, social and customer data piles on the doorstep of the corporation, and operational data sits in the creases and cracks between functions. While many companies invested in data warehouse technologies and advanced applications for optimization, a common complaint in qualitative interviews with business leaders is “I cannot get to my data.” One business leader likened it to a Hotel California where, “The data checks into the system, but does not check out.” In most companies with heterogeneous information technology landscapes, simple reporting is still a major problem.
In the face of growing data, companies struggle with the basics. The question is, “Why pursue a big data and analytics strategy if the company cannot do basis reporting?” No doubt about it, the current state of analytics is a barrier to building supply chain excellence. It is hard to have a data-driven discussion if you can’t get access to data.
Report on strategic rules of Information System for changing the bases of com...Md. Khukan Miah
Achieving advantages requires broad IS management and user dialogue plus imagination. The process is complicated by the fact that many IS products are strategic though the potential benefits are very subjective and not easily verified. Often a strict ROI focus by senior management may turn attention toward narrow, well-defined targets as opposed to broader strategic opportunities that are harder to analyze.
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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The world of search engine optimization (SEO) is buzzing with discussions after Google confirmed that around 2,500 leaked internal documents related to its Search feature are indeed authentic. The revelation has sparked significant concerns within the SEO community. The leaked documents were initially reported by SEO experts Rand Fishkin and Mike King, igniting widespread analysis and discourse. For More Info:- https://news.arihantwebtech.com/search-disrupted-googles-leaked-documents-rock-the-seo-world/
B2B payments are rapidly changing. Find out the 5 key questions you need to be asking yourself to be sure you are mastering B2B payments today. Learn more at www.BlueSnap.com.
Discover the innovative and creative projects that highlight my journey throu...dylandmeas
Discover the innovative and creative projects that highlight my journey through Full Sail University. Below, you’ll find a collection of my work showcasing my skills and expertise in digital marketing, event planning, and media production.
Recruiting in the Digital Age: A Social Media MasterclassLuanWise
In this masterclass, presented at the Global HR Summit on 5th June 2024, Luan Wise explored the essential features of social media platforms that support talent acquisition, including LinkedIn, Facebook, Instagram, X (formerly Twitter) and TikTok.
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Improving profitability for small businessBen Wann
In this comprehensive presentation, we will explore strategies and practical tips for enhancing profitability in small businesses. Tailored to meet the unique challenges faced by small enterprises, this session covers various aspects that directly impact the bottom line. Attendees will learn how to optimize operational efficiency, manage expenses, and increase revenue through innovative marketing and customer engagement techniques.
Rethinking information strategies information vs data
1. RETHINKING INFORMATION STRATEGIES
MANAGING INFORMATION, NOT DATA AS AN ORGANIZATONAL ASSET
In this second of the “Rethinking Information Strategies” series, we will go through why it is important
to focus on information and not data as an organizational asset.
Too many companies focus on data as an organizational asset, which is organized in a way that benefits
the supplier and not the consumer. For the benefitting of the consumer of information, it must be
aligned to the business processes intended to consume this information.
Unfortunately, those business processes for which information is intended to be aligned to change as
market forces change. And as the use of information moves up the food chain to more important and
strategic purposes, the alignment becomes more fleeting and requires a different level of care and
feeding than many organizations are equipped to handle.
SHIFTING FROM MANAGING DATA TO MANAGING INFORMATION
The shift is subtle. Most organizations have big data initiatives. The big data initiatives are devised to
optimize the storage of information, and not necessarily the consumption of information. A layer of
architecture that aligns big data to the consumption patterns of the most strategic business processes
would be devised as a means of extracting the maximum value of big data initiatives if they were
devised for consumption and not storage.
Many big data environments quickly become data swamps because there is no imperative from a
supply standpoint to decommission data in the big data environment because it is no longer aligned
with consumption patterns. However, this once aligned data leads to clutter, which challenges finding
what is necessary for consumption.
ACCOUNTABILITY FOR THE SHIFT
There are four key players who have accountability in the shift from managing the supply of data to
managing the consumption of information. They are:
• The Chief Data Officer, or the person responsible for understanding and enforcing the
alignment of the consumption patterns of information.
• The Data Asset Manager, which is a new role and is responsible for managing the storage and
consumption of data, WIP and information inventories. Most organizations would not argue a
need to have accountability of their working capital, but when it comes to information we have
become quite good at managing the cost side of the equation but not the inferred value of
information. The data asset manager has this accountability.
• The Data Governance Council, which has a shifted focus from perfecting the supply side of the
equation to perfecting the consumption side, namely eliminating impediments to consumption
of information. This could be information clutter, data quality prior to and after it’s alignment
as information, adherence of context (metadata) and other criteria.
2. • The Chief Information Officer, who is the owner and engineer for the machinery used to
transform the supplied data into consumable information. Information Inventory
ADOPTING THE NEW STRATEGY
The shift sounds small, but it is a major shift in the processes employed in most organizations. Most
organizations are focused on data, which is a cost of the organization. As a cost center, the focus of the
organization is to wrangle every possible ounce of cost out of the organization to do the least harm. In
many organizations, the Chief Data Officer, if they exist, is managed outside of the information
technology organization because it is realized that this should not be the focus of the CDO.
Shifting to managing the consumption has a value consideration to it, and changes information from a
cost center to a profit center of the organization. As a profit center, it becomes incumbent of the
technology arm of the organization to build and manage facilities that meter the use of information in a
way that can differentiate between information appearing on a report (which has marginal value) to
information used to potentially thwart a major disruption in the marketplace 9which has more
significant value associated with it).
Few if any organizations are equipped to manage information this way. But clues can be taken from
those who manage information as part of their revenue stream, namely those who use information for
identifying new revenue opportunities in the online business. These can be M&A opportunity
wranglers, online storefronts or online distribution route optimizers. All have the potential today of
attaching value to their use of information from a consumption side of the equation, whether they are
formally doing so today or not.
ABOUT MARK ALBALA
Mark Albala, the author of the Rethinking Information Strategies series, is President of InfoSight
Partners. Mark provides clients advisory, architecture and strategy services based on his deep expertise
of information strategy, governance and quality.
ABOUT INFOSIGHT PARTNERS
InfoSight Partners is a business services firm whose mission is to facilitate focus into the value of
information assets of an organization. This is accomplished through technology and finance services
delivered through InfoSight Partners. The principles of InfoSight Partners, Mark Albala and Lynn
Albala, provide both technology and financial advisory and other services to client organizations and
vendors that market to client organizations.