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Key to Data Monetization | @CloudExpo #IoT #BigData #Analytics #AI #DX #DigitalTransformation
Many organizations are associating data monetization with selling their data

Many organizations are associating data monetization with selling their data. But selling data is not a trivial task, especially for organizations whose primary business relies on its data. Organizations new to selling data need to be concerned with privacy and Personally Identifiable Information (PII), data quality and accuracy, data transmission reliability, pricing, packaging, marketing, sales, support, etc. Companies such as Nielsen, Experian and Acxiom are experts at selling data because that’s their business; they have built a business around gathering, aggregating, cleansing, aligning, packaging, selling and supporting data.

So instead of focusing on trying to sell your data, you should focus on monetizing the customer, product and operational insights that are gleaned from the data; insights that can be used to optimize key business and operational processes, reduce security and compliance risks, uncover new revenue opportunities, and create a more compelling customer and partner engagement.

For organizations seeking to monetize their customer, product and operational insights, the Analytic Profile is indispensible. While I have talked frequently about the concept of Analytic Profiles, I’ve never written a blog that details how Analytic Profiles work.  So let’s create a “Day in the Life” of an Analytic Profile to explain how an Analytic Profile works to capture and “monetize” your analytic assets.

Analytic Profiles
Analytic Profiles provide a storage model (think key-value store) for capturing the organization’s analytic assets in a way that facilities the refinement and sharing of those analytic assets across multiple business use cases. An Analytic Profile consists of metrics, predictive indicators, segments, scores, and business rules that codify the behaviors, preferences, propensities, inclinations, tendencies, interests, associations and affiliations for the organization’s key business entities such as customers, patients, students, athletes, jet engines, cars, locomotives, CAT scanners, and wind turbines (see Figure 1).

Figure 1: Analytic Profiles

Analytic Profiles enforce a discipline in the capture and re-use of analytics insights at the level of the individual key business entity (e.g., individual patient, individual student, individual wind turbine). The lack of an operational framework for capturing, refining and sharing the analytics can lead to:

  • Inefficient use of data engineering and data science resources
  • Analytics projects unattached to high value business initiatives
  • Limited organizational learning capture and application
  • Difficulty gaining organizational buy-in for investments in analytic technologies, resources, and skillsets
  • Difficulty building credibility as a trusted business advisor
  • Lack of re-usable assets that make future use cases more cost efficient and dramatically increase Return on Investment (ROI)

Let’s see how an Analytic Profile works.

Analytic Profiles in Action
Let’s say that you are the Vice President of Analytics at an organization that tracks individual purchase transactions via a registered on-line account and/or a loyalty program (e.g., retail, hospitality, entertainment, travel, restaurant, financial services, insurance). You’ve been asked to apply data and analytics to help the organization “increase same location sales” by 5%.

After executing a Vision Workshop (very smart move, by the way!) to identify, validate, prioritize and align the business stakeholders around the key business use cases, you’ve come up with the following business use cases for the “Increase Same Location Sales” business initiative:

  • Use Case #1: Improve Campaign Effectiveness
  • Use Case #2: Increase Customer Loyalty
  • Use Case #3: Increase Customer Store Visits
  • Use Case #4: Reduce Customer Attrition

“Improve Campaign Effectiveness” Use Case
To support the “Improve Campaign Effectiveness” use case, the data science team worked with the business stakeholders to brainstorm, test and confirm that they needed to build Demographic and Behavioral Segments for each individual customer. The Demographic segments are based upon customer variables such as age, gender, marital status, employment status, employer, income level, education level, college degrees, number of dependents, ages of dependents, home location, home value, work location and job title.  The Behavioral segments are based upon purchase and engagement transactions such as frequency of purchase, recency of purchase, items purchased, amount of money spent, coupons or rebates used, discounts applied, returns and consumer comments.

Figure 2 shows the Customer Analytic Profile for Customer WDS120356 resulting from the “Increase Campaign Effectiveness” use case.

Figure 2: Improve Campaign Effectiveness

Note: a customer will NOT be in a single Demographic or Behavioral segment, but will likely reside in numerous different Demographic and Behavioral segments based upon combinations of the demographic attributes and purchase activities.

As a result of this use case, we have created and captured in the Analytic Profile numerous demographic and behavioral segments for each individual customer. These demographic and behavioral segments are now available across different use cases.

“Improve Customer Loyalty” Use Case
The next use case is “Increase Customer Loyalty.” The data science team again begins the process by brainstorming with the business stakeholders to “identify the variables and metrics that might be better predictors of customer loyalty.” The data science team starts the analytics process by re-using the data that was placed into the data lake for use case #1, but gathers additional data to support the development, testing and refinement of a Customer Loyalty Score.

As part of their analytic modeling process, the data science team decides that the Behavioral Segments created for use case #1 can be re-used to support the “Increase Customer Loyalty” use case, but find that they can improve the predictive capabilities of the Behavioral Segments with the additional data.

Consequently, the data science team completes two tasks in support of the “Increase Customer Loyalty” use case:

  • Creates a new Customer Loyalty Score comprised of data from the use case #1 plus new data sources
  • Improves the predictive capabilities of the pre-existing Behavioral Segments (now version controlled as version 1.1)

Figure 3 shows the updated Customer Analytic Profile for Customer WDS120356 resulting from the “Increase Customer Loyalty” use case.

Figure 3: Increase Customer Loyalty Use Case

It is critical to note that the beneficiary of the improved Behavioral Segments – at no additional cost – is use case #1: Improve Campaign Effectiveness. That is, the performance and results of the “Increase Campaign Effectiveness” use case just improved at no additional cost!

In order to realize this benefit, the analytics captured in the Analytic Profiles must be treated like software and include support for software development techniques such as check-in/check-out, version control and regression testing (using technologies such as Jupyter Notebooks and GitHub).

“Increase Customer Store Visits” Use Case
Let’s go through one more use case: “Increase Customer Store Visits.” The data science team again begins the process by brainstorming with the business stakeholders to “identify the variables and metrics that might be better predictors of customer visits.” The data science team again starts the analytics process by re-using the data that was placed into the data lake for use cases #1 and #2, but gathers additional data to support the development, testing and refinement of a Customer Frequency Index.

As part of their analytic modeling process, the data science team again decides that the Behavioral Segments updated for use case #2 can be re-used to support the “Increase Customer Store Visits” use case, and they find that they can again improve the predictive capabilities of the Behavioral Segments with the additional data necessary to support the “Increase Customer Store Visits” use case.

Figure 4 shows the updated Customer Analytic Profile for Customer WDS120356 resulting from the “Increase Customer Store Visits” use case.

Figure 4: Increase Store Visits Use Case

Again, the beneficiary of the updated Behavioral Segments – at no additional cost – are use cases #1 and #2 that find that the performance and results of those use case just improved at no additional cost.

Analytic Profiles Summary
Proceeding use case-by-use case, the Customer Analytic Profiles gets fleshed out and provide the foundation for data monetization through the results of improved business and operational processes and reduced security and compliance risks (see Figure 5).

Figure 5:  Fully Functional Customer Analytic Profile

The Analytic Profiles also provide the foundation for identifying new revenue opportunities; to understand your customer and product usage behaviors, tendencies, inclinations and preferences so well that you can identify unmet customer needs or new product usage scenarios for new services, new products, new pricing, new bundles, new markets, new channels, etc.

Embracing the concept of Analytic Profiles creates an operational framework for the capture, refinement and re-use of the organization’s analytic assets. This enables:

  • Leveraging analytic insights about key business entities across multiple business use cases.
  • Developing benchmarks that over time contribute to the optimization of future decisions.
  • Developing repeatable analytic processes to accelerate the adoption of analytics within your organization.
  • Justifying investment in analytics tools and data scientists to further increase the economic value of your data.
  • Extending the value of your analytic efforts by making your analytics consumable to other business stakeholders.
  • Gaining a better understand of what data you “don’t have” but “could have.”

Analytic Profiles help organization to prioritize and align data science resources to create actionable insights that can be re-used across the organization to optimize key business and operational processes, reduce cyber security risks, uncover new monetization opportunities and provide a more compelling, more prescriptive customer and partner experience.

So while you should not focus on selling your data (because it’s hard to quantify the value of your data to others), instead look for opportunities to sell the analytic insights (e.g., industry indices, customer segmentation, product and service cross-sell/up-sell recommendations, operational performance benchmarks) that support your target market’s key decisions. Your target market will likely pay for analytic insights that help them make better decisions and uncover new revenue opportunities.

The post Analytic Profiles: Key to Data Monetization appeared first on InFocus Blog | Dell EMC Services.

Read the original blog entry...

About William Schmarzo
Bill Schmarzo, author of “Big Data: Understanding How Data Powers Big Business”, is responsible for setting the strategy and defining the Big Data service line offerings and capabilities for the EMC Global Services organization. As part of Bill’s CTO charter, he is responsible for working with organizations to help them identify where and how to start their big data journeys. He’s written several white papers, avid blogger and is a frequent speaker on the use of Big Data and advanced analytics to power organization’s key business initiatives. He also teaches the “Big Data MBA” at the University of San Francisco School of Management.

Bill has nearly three decades of experience in data warehousing, BI and analytics. Bill authored EMC’s Vision Workshop methodology that links an organization’s strategic business initiatives with their supporting data and analytic requirements, and co-authored with Ralph Kimball a series of articles on analytic applications. Bill has served on The Data Warehouse Institute’s faculty as the head of the analytic applications curriculum.

Previously, Bill was the Vice President of Advertiser Analytics at Yahoo and the Vice President of Analytic Applications at Business Objects.

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Emcien

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Cognitive Scale

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Cisco

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Systems Services Inc.

COLLISON
Apcera

PRABHU
OpenCrowd

LYNN
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SWARTZ
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HAM

SIOS

WILLIS
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MURPHY
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GetClouder

DIETZE
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MPLE

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MAZZUCCO
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CARTER
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Cloud Expo Silicon Valley All-Star Speakers

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SINGH
Bigdata

BEACH
SendGrid

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DE SOUZA
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PATTATHIL
Harbinger

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Aria Systems

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BIANCO
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PROCTOR
NuoDB

DUGGAL
EnterpriseWeb

TEGETHOFF
Appcore

BRUNOZZI
VMware

HICKENS
Parasoft

KLEBANOV
Cisco

PETERS
Esri

GOLDBERG
Vormetric

CUMBER-
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Dimension

ROSENDAHL
Quantum

LOOMIS
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BRUNO
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HANNON
SoftLayer

JACKSON
SoftLayer

HOCH
Virtustream

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PAQUIN
OnLive

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PLESE
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Verizon

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Transparent Cloud Computing

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Transparent Cloud Computing

NATH
GE

GOKCEN
GE

STOICA
Databricks

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Pivotal Software


Testimonials
This week I had the pleasure of delivering the opening keynote at Cloud Expo New York. It was amazing to be back in the great city of New York with thousands of cloud enthusiasts eager to learn about the next step on their journey to embracing a cloud-first worldl."
@SteveMar_Msft
General Manager of Window Azure
 
How does Cloud Expo do it every year? Another INCREDIBLE show - our heads are spinning - so fun and informative."
@SOASoftwareInc
 
Thank you @ThingsExpo for such a great event. All of the people we met over the past three days makes us confident IoT has a bright future."
Yasser Khan
CEO of @Cnnct2me
 
One of the best conferences we have attended in a while. Great job, Cloud Expo team! Keep it going."

@Peak_Ten


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@CloudExpo Blogs
The “Internet of Things” is an exciting area of tech, one in which industry experts estimate there will be more than 30 billion connected IoT devices by 2020. IoT is the inter-networking and instrumentation of physical devices – everything from streets, cars, factories, power grids, ice caps, satellites, and clothing to phones, microwaves, milk containers, planets, human bodies, etc. IoT creates an opportunity to measure, collect and analyze an ever-increasing variety of behavioral statistics. That being said, data, and more importantly insight into the data, is key for enhanced business val...
In an attempt to put the patient first in healthcare, Congress and President Obama in 2015 approved a bipartisan bill for United States healthcare reform. The bill is known as “Medicare Access and CHIP Reauthorization Act of 2015,” or MACRA. Among the major provisions of MACRA is the Quality Payment Program. Under the Quality Payment Program, physicians and nurses receive positive, neutral or negative Medicare payment adjustments based upon a “Patient Satisfaction Score,” that is, patient satisfaction scores have a direct impact on how physicians, physician assistants, nurses, and hospital’s g...
The high barrier to entry prevents many companies from tapping into the full potential of machine learning. But what if you could make it more accessible? We’re in the midst of a data explosion, with today’s enterprises amassing goldmines of information (25 quintillion bytes of data every day, according to some reports). But what exactly are they doing with this data? Considering the volume of data being collected is quickly becoming unmanageable, now is a good time to shift from manual machine learning to a cognitive approach. This enables businesses to better capitalize on their data and fa...
Our work, both with clients and with tools, has lead us to wonder how it is that organizations are handling compliance issues in the cloud. The big cloud vendors offer compliance for their infrastructure, but the shared responsibility model requires that you take certain steps to meet compliance requirements. Which lead us to start poking around a little more. We wanted to get a picture of what was available, and how it was being used. There is a lot of fluidity in this space, as in all things cloud. The fact that DevOps Security plays into the cloud compliance model – particularly in dynamic ...
Gaining visibility in today’s sprawling cloud infrastructure is complex and laborious, involving drilling down into tools offered by various cloud services providers. Enterprise IT organizations need smarter and effective tools at their disposal in order to address this pertinent problem. Gaining a 360 - degree view of the cloud costs requires collection and analysis of the cost data across all cloud infrastructures used inside an enterprise.
The 22nd International Cloud Expo | 1st DXWorld Expo has announced that its Call for Papers is open. Cloud Expo | DXWorld Expo, to be held June 5-7, 2018, at the Javits Center in New York, NY, brings together Cloud Computing, Digital Transformation, Big Data, Internet of Things, DevOps, Machine Learning and WebRTC to one location. With cloud computing driving a higher percentage of enterprise IT budgets every year, it becomes increasingly important to plant your flag in this fast-expanding business opportunity. Submit your speaking proposal today!
The goal of Microservices is to improve software delivery speed and increase system safety as scale increases. Microservices being modular these are faster to change and enables an evolutionary architecture where systems can change, as the business needs change. Microservices can scale elastically and by being service oriented can enable APIs natively. Microservices also reduce implementation and release cycle time and enables continuous delivery. This paper provides a logical overview of the Microservices Reference Architecture that highlights various sub systems needed to support Microservic...
The notion of improving operational efficiency is conspicuously absent from the healthcare debate - neither Obamacare nor the newly proposed GOP plan discusses the impact that a step-function improvement in efficiency could have on access to healthcare (through more capacity), quality of healthcare services (through reduced wait times for patients) or cost (through better utilization of scarce, expensive assets).
Most of us understand that artificial intelligence (AI) offers opportunities for productivity improvements in the form of speed, automation, standardized actions and responses, plus the opportunity for continuous improvements via machine learning. These opportunities are enabled by data inputs that are analyzed and processed through AI algorithms that execute a desired decision and action. For all of the great capabilities and benefits that AI can provide, there is also a potential dark side. AI solutions can easily codify our prejudices, bias, gender stereotypes and promote injustices intenti...
Blockchain offers impeccable security with its cryptography-based decentralized system as well as the plethora of possible uses retailers could exploit in the near future. In a world of increasing cyberattacks, internet fraud and online hacking, blockchain comes as a breath of fresh air. With its encrypted data and decentralized network system, it's a thorn in every hacker's side. Generally being associated with the finance sector, blockchain is now taking retail by storm. It's on a course that will change the retail industry as we know it. But how exactly is it going to achieve such a feat?
Gone are the days when application development was the daunting task of the highly skilled developers backed with strong IT skills, low code application development has democratized app development and empowered a new generation of citizen developers. There was a time when app development was in the domain of people with complex coding and technical skills. We called these people by various names like programmers, coders, techies, and they usually worked in a world oblivious of the everyday priorities of the business world. However, with the passage of time, this scenario is much more democr...
It’s conference season and, as you might expect, Jason and I have been on the road covering a bunch of them. It’s always great to see what the disruptive players in the market are doing — and this year did not disappoint. But there is one thing that repeatedly happens that just gets under my skin: transformation-washing. As Jason explained in a Forbes article over a year ago, ‘washing’ is when a vendor (or pundit) applies a buzzword loosely in an overt attempt to attach themselves to its buzz. And transformation-washing is rampant.
Networks have become large, complex entities that are increasingly difficult to manage and control. Security, audit, risk and compliance professionals know that their organizations rely on them for effective risk management, control and governance processes that are essential to the safety of their network environment. Yet compliance and security are more challenging than ever before as additional layers are added to this environment. One of the challenges lies in the fact that there is an ongoing, huge access gap in network security and compliance – and it has been residing within the enviro...
Some journey to cloud on a mission, others, a deadline. Change management is useful when migrating to public, private or hybrid cloud environments in either case. For most, stakeholder engagement peaks during the planning and post migration phases of a project. Legacy engagements are fairly direct: projects follow a linear progression of activities (the “waterfall” approach) – change managers and application coders work from the same functional and technical requirements. Enablement and development mirror one another, progressing from proof-of-concept planning to final product delivery. Exce...
While Artificial Intelligence (AI) may not be a new concept, its contribution to automation may just change the face of business. AI's conception dates as far back as 1950, when Alan Turing proposed the Turing test in order to evaluate a machine's ability to exhibit intelligent behavior. Fast-forward a couple of decades and research led to the creation of well-known theoretical tools such as Fuzzy Logic, Bayesian Networks, Markov Models and Neural Networks. Concurrently, new types of programming languages such as Prolog, LISP and Smalltalk set the scene for most of the modern interpreted langu...
Fingerspitzengefühl: A German word used to describe the ability to maintain attention to detail in an ever-changing operational and tactical environment by maintaining real-time situational awareness. The term is synonymous with the English expression of "keeping one's finger on the pulse". The problem with fingerspitzengefühl traditionally, in addition to pronouncing it, has been it is hard for an individual to scale up. Today that is changing. In a world of sensors, AI and mobile devices, having real-time situational awareness is far easier than ever before. In fact, today the challenge i...
Making informed network investment decisions about emerging technologies such as network function virtualization (NFV) and software-defined networking (SDN) can help evolve the network to keep pace with the innovations of the devices and people it’s connecting. As you work with business leaders to make decisions about upgrading your infrastructure with these networking developments, it’s important to understand the similarities, differences, and benefits of dual NFV and SDN implementation. With their ability to offer a new way to design, deploy, and manage the network and its services, NFV a...
For DevOps teams, the concepts behind service-oriented architecture (SOA) are nothing new. A style of software design initially made popular in the 1990s, SOA was an alternative to a monolithic application; essentially a collection of coarse-grained components that communicated with each other. Communication would involve either simple data passing or two or more services coordinating some activity. SOA served as a valid approach to solving many architectural problems faced by businesses, as applications could be developed by more teams working in parallel and more productively by reusing orig...
Many IT organizations have come to learn that leveraging cloud infrastructure is not just unavoidable, it’s one of the most effective paths for IT organizations to become more responsive to business needs. Yet with the cloud comes new challenges, including minimizing downtime, decreasing the cost of operations, and preventing employee burnout to name a few. As companies migrate their processes and procedures to their new reality of a cloud-based infrastructure, an incident management solution can and should be adopted to help overcome these challenges. This is particularly true when larger ...
We’re seeing an emerging trend in the cloud computing world. I’ve been referring to it as cloud fatigue, but it’s more commonly known as repatriation, or moving workloads from the cloud back to on-prem locations. According to a recent 451 Research report, over 21 percent of organizations have plans to pull back from the cloud and return to an on-prem infrastructure in 2017. Considering the vast growth of cloud adoption over the last several years, what’s behind this trend?