Upload Image

From file

Submit URL

Cancel Upload

Log Out

Are you sure you want to log out?

Cancel Log out

About

Mediafly is a mobile sales enablement solution that enhances how brands engage prospective buyers. By using Mediafly's technology, marketing and sales teams are able to deliver custom, dynamic sales presentations quickly and efficiently, engaging customers with insights that are relevant to them.

Mediafly ValueStory v
Copyright , All rights reserved

 

Request Support Privacy Policy Terms of Use Visit mediafly.com Follow @mediafly

Close

Application Settings

High Contrast Mode

Off On

Show Introduction

Off On

Request full screen mode when opening app

Off On

Toggle Full Screen

Switch

Show Instructional Overlays

Reset All

Close

Error Report

Named Ranges

Currency List

Duplicate Events

Unbranded Elements

Spelling Errors

close

Audit Log

Select an entry to revert the value of this input back to any previous state

Cancel Revert

Get your report

Tell us where to email your report and we will send it off

First name

Last name

Title

Phone

Country

State

Email

Please Visit IBM Privacy Policy Here.

Yes, I would like to stay in touch with IBM Cloud Pak for Data by email.

I would like to be contacted by an IBM representative to discuss my assessment.

Cancel Email report

Assumptions

Edit these assumptions to customize your value analysis

Currency Afghanistan Afghanis Aland European Euro Albania Leke Algeria Dinars American Samoa USD Andorra European Euro Angola Kwanza Anguilla EC Dollar Antigua and Barbuda EC Dollar Argentina Pesos Armenia Drams Aruba Florin Australia Dollars Austria European Euro Azerbaijan New Manats Bahamas Dollars Bahrain Dinars Bangladesh Taka Barbados Dollars Belarus Rubles Belgium European Euro Belize Dollars Benin CFA Bermuda Dollars Bhutan Ngultrum Bolivia Bolivianos Bosnia Herzegovina C. Marka Botswana Pulas Bouvet Island Brazil Reais British Indian Ocean Territory USD British Virgin Islands USD Brunei Dollars Bulgaria Leva Burkina Faso West African CFA Burundi Francs Cambodia Riels Cameroon CFA BEAC Francs Canada Dollars Cayman Islands Dollars Central African Republic CFA BEAC Francs Chad CFA BEAC Francs Chile Pesos China Yuan Renminbi Christmas Island AU Dollars Cocos (Keeling) Islands AU Dollars Colombia Pesos Comoros Francs Congo/Kinshasa Francs Cook Islands NZ Dollars Costa Rica Colones Cote d Ivoire (Ivory Coast) West African CFA Croatia Kuna Cuba Pesos Cuba Convertible Pesos Cyprus European Euro Czech Republic Koruny Denmark Kroner Djibouti Francs Dominica EC Dollar Dominican Republic Pesos Ecuador USD Egypt Pounds El Salvador USD Equatorial Guinea Central African CFA Eritrea Nakfa Estonia Kroon Ethiopia Birr Falkland Islands Pounds Faroe Islands Kroner Fiji Dollars Finland European Euro France European Euro French Guiana European Euro French Polynesia French Polynesia Franc Gabon CFA BEAC Francs Gambia Dalasi Georgia Lari Germany European Euro Ghana Cedis Gibraltar Pounds Greece European Euro Greenland Krone Grenada EC Dollar Guadeloupe European Euro Guam USD Guatemala Quetzales Guernsey Pounds Guinea Francs Guinea-Bissau West African CFA Guyana Dollars Haiti Gourdes Heard Island and McDonald Islands AU Dollars Honduras Lempiras Hong Kong Dollars Hungary Forint Iceland Kronur India Rupees Indonesia Rupiahs Iran Rials Iraq Dinars Ireland European Euro Isle of Man Pounds Israel New Shekels Italy European Euro Jamaica Dollars Japan Yen Jersey Pounds Jordan Dinars Kazakhstan Tenge Kenya Shillings Kiribati AU Dollars Kuwait Dinars Kyrgyzstan Soms Laos Kips Latvia Lati Lebanon Pounds Lesotho Maloti Liberia Dollars Libya Dinars Liechtenstein Swiss Franc Lithuania Litai Luxembourg European Euro Macau Patacas Macedonia Denars Madagascar Ariary Malawi Kwachas Malaysia Ringgits Maldives Rufiyaa Mali West African CFA Malta Lira Marshall Islands USD Martinique European Euro Mauritania Ouguiyas Mauritius Rupees Mayotte European Euro Mexico Pesos Micronesia USD Moldova Lei Monaco European Euro Mongolia Tugriks Montenegro European Euro Montserrat EC Dollar Morocco Dirhams Mozambique Meticais Myanmar Kyats Namibia Dollars Nauru AU Dollars Nepal Rupees Netherlands Antilles Guilders New Caledonia French Pacific Franc New Zealand Dollars Nicaragua Cordobas Niger West African CFA Nigeria Nairas Niue NZ Dollars Norfolk Island AU Dollars North Korea Won Northern Mariana Islands USD Norway Kroner Oman Rials Pakistan Rupees Palau USD Panama Balboas Papua New Guinea Kina Paraguay Guarani Peru Nuevos Soles Philippines Pesos Pitcairn Islands NZ Dollars Poland Zlotych Portugal European Euro Puerto Rico USD Qatar Riyals Reunion European Euro Romania New Lei Russia Rubles Rwanda Francs Saint Helena Pounds Saint Kitts and Nevis EC Dollar Saint Lucia EC Dollar Saint Pierre and Miquelon European Euro Saint Vincent and the Grenadines EC Dollar Samoa Tala San Marino European Euro São Tome and Principe Dobras Saudi Arabia Riyals Senegal West African CFA Serbia Dinars Seychelles Rupees Sierra Leone Leones Singapore Dollars Slovakia European Euro Slovenia European Euro Solomon Islands Dollars Somalia Shillings South Africa Rand South Georgia and South Sandwich Islands Pound South Korea Won Spain European Euro Sri Lanka Rupees Sudan Pounds Suriname Dollars Svalbard Krone Swaziland Emalangeni Sweden Kronor Switzerland Francs Syria Pounds Taiwan New Dollars Tajikistan Somoni Tanzania Shillings Thailand Baht Timor-Leste (East Timor) USD Togo Tokelau NZ Dollars Tonga Pa Anga Trinidad and Tobago Dollars Tunisia Dinars Turkey Lira Turkmenistan New Manats Turks and Caicos Islands USD Tuvalu Dollars U.S. Virgin Islands USD Uganda Shillings Ukraine Hryvnia United Arab Emirates United Kingdom Pounds United States Dollars Uruguay Pesos Uzbekistan Sums Vanuatu Vatu Vatican City European Euro Venezuela Bolivares Vietnam Dong Wake Island USD Wallis and Futuna French Pacific Franc Yemen Rials Zambia Kwacha Zimbabwe Dollars Reduce Cost Productivity Cost (Data Engineer, Data Stewards, Administrators) Number of users Fully burdened salary per user (annual) Productivity improvement percentage Productivity Cost (Data Scientists) Number of users Fully burdened salary per user (annual) Productivity improvement percentage Infrastructure Cost (Software and Hardware) - PLATFORM IMPACT Number of IT Users (Data Engineer/Steward/Analyst/Scientist) Number of LOB Users License Cost per IT User Avoided License Cost per LOB User Avoided Number of Servers Annual Server Refresh Rate Average cost per Server Infrastructure cost reduction benefit (Utilization) Reduce Risk If a compliance and regulatory risk is realized, the potential cost Reputational Risk potential cost Probability of regulatory risk event Probability of reputational risk event Increase revenue Maximum potential improvement of time-to-value impact Improvement Percentage due to increased Trust in AI Number of AI Initiatives to launch in 12 months Average number of months to launch an AI initiative Average Opportunity Cost to the business for every month of delay

close

You Can't have AI without IA

Research from MIT Sloan indicates that 85% of organizations view AI as a strategic priority, however 51% of organizations are struggling with operationalizing, sustaining and scaling their AI initiatives.

Moving beyond experimentation is a challenge, especially when you don’t have the right Information Architecture.

You can't have AI without the right IA. And to get IA right you need to improve your capabilities to overcome these key challenges:

• Data- 60% are challenged in managing data quality
• Skills- 62% are challenged to acquire the right talent and build skills
• Trust- 62% need an approach to AI production readiness

To accelerate your AI journey, modernizing IA is required, but how do you get there best?

Begin Your IA Journey

Do not show this message again

You can use this IA Modernization Journey tool to help you:

Plot where you are on your IA Journey

Compare where you are to your peers

Provide a roadmap of best steps to modernize your IA

Assess the potential business value outcomes from IA modernization plans

Only with Company XYZ

The expected investment required to implement Company XYZ

Categories

Initial

Year 1

Year 2

Year 3

Total

Licensing costs

Initial

Year 1

Year 2

Year 3

Total

Persistence module costs

Initial

Year 1

Year 2

Year 3

Total

Initial Internal Implementation/Integration Costs

Initial

Year 1

Year 2

Year 3

Total

Ongoing Internal Implementation/Integration Costs

Initial

Year 1

Year 2

Year 3

Total

Initial

Year 1

Year 2

Year 3

Total

Total

Initial

Year 1

Year 2

Year 3

Total

CANCEL SUBMIT INVESTMENT

Your Organizations Profile

Tell us a little about your organization to get the assessment started. This profile information is used to find the best peers for comparison and setup default metrics for your personalized value analysis.

Name of your organization

Closest matching industry

Your organization's location

Select One United States Afghanistan Albania Algeria Andorra Angola Antigua and Barbuda Argentina Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bhutan Bolivia, Plurinational State of Bosnia and Herzegovina Botswana Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Central African Republic Chad Chile China Colombia Comoros Congo Costa Rica Côte d'Ivoire Croatia Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Eritrea Estonia Ethiopia Fiji Finland France Gabon Gambia Georgia Germany Ghana Greece Grenada Guatemala Guinea Guinea-Bissau Guyana Haiti Honduras Hungary Iceland India Indonesia Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Kiribati Korea, Republic of Kuwait Kyrgyzstan Latvia Lebanon Lesotho Liberia Libya Liechtenstein Lithuania Luxembourg Macedonia, The former Yugoslav Republic of Madagascar Malawi Malaysia Maldives Mali Malta Marshall Islands Mauritania Mauritius Mexico Micronesia, Federated States of Moldova, Republic of Mongolia Montenegro Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway Oman Pakistan Palau Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Qatar Romania Russian Federation Rwanda Saint Helena, Ascension and Tristan da Cunha Saint Kitts and Nevis Saint Vincent and the Grenadines Samoa San Marino Sao Tome and Principe Saudi Arabia Senegal Serbia Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa Spain Sri Lanka Suriname Swaziland Sweden Switzerland Taiwan Tajikistan Tanzania, United Republic of Thailand Timor-Leste Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kingdom Uruguay Uzbekistan Vanuatu Venezuela, Bolivarian Republic of Yemen Zambia Zimbabwe

Annual revenue for your organization (in millions)

Your role

Select One Line of Business Executive CIO/CTO Business Analyst IT Manager Data Scientist Data Engineer Enterprise Architect Developer Partner IBMer Other

Specify other

Number of employees

How fast are you growing?

Slower than peers

Faster than peers

Assumptions

The Ladder to AI

Collect

Make data simple and accessible

Organize

Create a business-ready analytics foundation

Analyze

Build and scale AI with trust and transparency

Infuse

Operationalize AI throughout the business

Modernize

Make your data ready for an AI and hybrid cloud world

Infuse

Your Responses Peer Comparison

Operationalize AI throughout the business. Indicate your current capabilities and maturity, and see your score / compare to your peers.

None

(0)

Ad-hoc

(1)

Standardized

(2)

Actively Managed

(3)

Optimizing

(4)

N/A

(5)

How effectively do you integrate intelligent search in to business facing applications to uncover hidden insights through use of Natural Language Processing and Machine Learning

None

Ad-hoc

Standardized

Actively
Managed

Optimizing

N/A

To what extent have you implemented AI / ML based Planning/Forecasting solutions to integrate data silos and create more accurate insights?

None

Ad-hoc

Standardized

Actively
Managed

Optimizing

N/A

How effectively have you leveraged AI and Machine Learning within your business intelligence practice for a comprehensive view of your enterprise

None

Ad-hoc

Standardized

Actively
Managed

Optimizing

N/A

How effectively have you leveraged AI Assitants both internally and externally for Call Center modernization, Employee Self Service, and Customer Self Service.

None

Ad-hoc

Standardized

Actively
Managed

Optimizing

N/A

Your Organization

Your peer average

None

(0)

Ad-hoc

(1)

Standardized

(2)

Actively Managed

(3)

Optimizing

(4)

N/A

(5)

How effectively do you integrate intelligent search in to business facing applications to uncover hidden insights through use of Natural Language Processing and Machine Learning

To what extent have you implemented AI / ML based Planning/Forecasting solutions to integrate data silos and create more accurate insights?

How effectively have you leveraged AI and Machine Learning within your business intelligence practice for a comprehensive view of your enterprise

How effectively have you leveraged AI Assitants both internally and externally for Call Center modernization, Employee Self Service, and Customer Self Service.

Infuse

Most organizations are still in the early days of determining how and where to use AI to advance their business agenda. But, interest is growing, largely because AI has the potential to solve one of the biggest challenges we face: we're drowning in data – 2.5 quintillion bytes – generated every day, but we're starved for insights.

AI helps us take advantage of all this data, much of which is dark and inaccessible, and make better decisions from the insights it can produce, while creating net-new or augmenting existing workflows across the entire organization.

Your Organization

Your Peers

Compared to  of your peers in the  industry

Building on projects with thousands of organizations around the world, we've observed that organizations choose to:

• Speed time to value with pre-built AI apps for common use case (e.g., customer service, financial planning)
• Automate knowledge work and business processes
• Employ AI-assisted business intelligence and data visualization
• Automate planning, budgeting and forecasting analytics
• Customize with Industry vertical AI-driven frameworks
• Innovate with new business models intelligently powered by AI

Solutions you may consider to drive improvements include:

• IBM Watson Assistant
• IBM Cognos Analytics
• IBM Planning Analytics
• IBM Watson Discovery

Analyze

Your Responses Peer Comparison

Build and scale AI with trust and transparency. Indicate your current capabilities and maturity, and see your score / compare to your peers.

None

(0)

Ad-hoc

(1)

Standardized

(2)

Actively Managed

(3)

Optimizing

(4)

N/A

(5)

Is your enterprise able to leverage data timely to make better decisions, create better outcomes and develop key insights quickly?

None

Ad-hoc

Standardized

Actively
Managed

Optimizing

N/A

How effectively do your knowledge workers (Data Scientists/Business Analysts) build, run, manage machine learning models?

None

Ad-hoc

Standardized

Actively
Managed

Optimizing

N/A

Does your company have a unified and open platform for analytics and/or data science that enables both experienced data scientists and your business analysts to create AI models available on any cloud, on premises or both?

None

Ad-hoc

Standardized

Actively
Managed

Optimizing

N/A

To what extend are you able to mitigate bias and explain outputs within Machine Learning models?

None

Ad-hoc

Standardized

Actively
Managed

Optimizing

N/A

Your Organization

Your peer average

None

(0)

Ad-hoc

(1)

Standardized

(2)

Actively Managed

(3)

Optimizing

(4)

N/A

(5)

Is your enterprise able to leverage data timely to make better decisions, create better outcomes and develop key insights quickly?

How effectively do your knowledge workers (Data Scientists/Business Analysts) build, run, manage machine learning models?

Does your company have a unified and open platform for analytics and/or data science that enables both experienced data scientists and your business analysts to create AI models available on any cloud, on premises or both?

To what extend are you able to mitigate bias and explain outputs within Machine Learning models?

Analyze

Once an organization has been able to collect their data and organize it in a trusted, unified view, they can now tap into that data to build and scale AI models across their business.

This allows companies like yours to glean insights from all their data, no matter where it resides, and engage with AI to transform their business -- putting themselves at a clear competitive advantage.

Your Organization

Your Peers

Compared to  of your peers in the  industry

You need a set of modular components, flexible environments and tools that make analyzing data and building AI models easier and more accessible for clients. For AI to thrive, and for businesses to reap its benefits, it is imperative that clients trust their AI systems. They need that trust in order to fully scale and automate AI across their enterprise organization. Key benefits of an AI system include:

• Everything you need to build and deploy AI models, fully integrated
• Based on open source frameworks, supporting a multicloud environment
• Full end-to-end automated lifecycle, enabling trust and transparency

Solutions you may consider to drive improvements include:

• IBM Watson Studio
• IBM Watson Machine Learning
• IBM Watson OpenScale

Organize

Your Responses Peer Comparison

Create a business-ready analytics foundation. Indicate your current capabilities and maturity, and see your score / compare to your peers.

None

(0)

Ad-hoc

(1)

Standardized

(2)

Actively Managed

(3)

Optimizing

(4)

N/A

(5)

Does your enterprise have a trusted inventory for data (data catalog) across structured and unstructured sources, enabling self-service data access, supported by a common business glossary, automatic quality scoring and lineage?

None

Ad-hoc

Standardized

Actively
Managed

Optimizing

N/A

Does your business have data ingestion (batch and real-time) integrated with a data catalog enabling your consumers with ease of access to valued-quality data?

None

Ad-hoc

Standardized

Actively
Managed

Optimizing

N/A

Are your business users able to quickly refine, profile and transform data without technical skills or having to make frequent requests to IT?

None

Ad-hoc

Standardized

Actively
Managed

Optimizing

N/A

Does your organization have the ability to use AI in automatically applying policies, rules, and classification to all relevant enterprise data in order minimize the traditionally manual efforts of governing information for optimal use and ensuring its security and privacy compliance?

None

Ad-hoc

Standardized

Actively
Managed

Optimizing

N/A

Your Organization

Your peer average

None

(0)

Ad-hoc

(1)

Standardized

(2)

Actively Managed

(3)

Optimizing

(4)

N/A

(5)

Does your enterprise have a trusted inventory for data (data catalog) across structured and unstructured sources, enabling self-service data access, supported by a common business glossary, automatic quality scoring and lineage?

Does your business have data ingestion (batch and real-time) integrated with a data catalog enabling your consumers with ease of access to valued-quality data?

Are your business users able to quickly refine, profile and transform data without technical skills or having to make frequent requests to IT?

Does your organization have the ability to use AI in automatically applying policies, rules, and classification to all relevant enterprise data in order minimize the traditionally manual efforts of governing information for optimal use and ensuring its security and privacy compliance?

Organize

Once an organization is able to collect their data and make it accessible throughout their business, the next step is to make sure it’s organized in a trusted, business-ready foundation. Many businesses underestimate the pitfalls that poor data governance can create. In search of instant insights, businesses prioritize data access and analysis over data governance and quality.

Leaders can’t be confident in their AI without ensuring data is trustworthy, complete, and consistent. Data is the bread and butter of AI, and the quality of that data, directly affects the results of your AI. Organizations need their data to be organized, catalogued, and governed to ensure that only the people who should be able to access it, can.

Your Organization

Your Peers

Compared to  of your peers in the  industry

It’s clear that data governance is critical for a successful AI transformation, and as such, it is important to advance your digital transformation by building a unified DataOps and governance foundation to deliver trusted, business-ready data. This foundation is one that helps:

• Profile, cleanse, and catalog all types of data
• Manage data with built-in protection and compliance
• Enable policy-driven visibility, detection, and reporting
• Manage data at all stages of the information lifecycle, from creation to deletion

Solutions you may consider to drive improvements include:

• IBM InfoSphere family
• IBM Watson Knowledge Catalog

Collect

Your Responses Peer Comparison

Make data simple and accessible. Indicate your current capabilities and maturity, and see your score / compare to your peers.

None

(0)

Ad-hoc

(1)

Standardized

(2)

Actively Managed

(3)

Optimizing

(4)

N/A

(5)

Does your business have central access to all of the data your enterprise has and needs, regardless of the source, location, type or processes?

None

Ad-hoc

Standardized

Actively
Managed

Optimizing

N/A

Are you able to create on-demand, fit-for-purpose repositories for various types of data (streaming, transactional and unstructured data)?

None

Ad-hoc

Standardized

Actively
Managed

Optimizing

N/A

Can you automatically discover and use data from across the enterprise?

None

Ad-hoc

Standardized

Actively
Managed

Optimizing

N/A

Your Organization

Your peer average

None

(0)

Ad-hoc

(1)

Standardized

(2)

Actively Managed

(3)

Optimizing

(4)

N/A

(5)

Does your business have central access to all of the data your enterprise has and needs, regardless of the source, location, type or processes?

Are you able to create on-demand, fit-for-purpose repositories for various types of data (streaming, transactional and unstructured data)?

Can you automatically discover and use data from across the enterprise?

Collect

For too long, data has been held captive within systems of record, and isolated by the rigid platform choices, segregated business functions, and data types. The result is splintered views and difficulty accessing data, making it impossible to attempt to gain true analytical insight, and this is just today.

These challenges are made worse as your businesses evolve. Data science, machine learning, and deep learning are made moot because insights are only as good as the access to supporting data.

Your Organization

Your Peers

Compared to  of your peers in the  industry

A hybrid data management strategy can not only relieve some of the current challenges around data, but also provide access to more data to fuel smarter AI. To improve, you need a proper hybrid data-management strategy in order to ensure a strong foundation for AI, one that provides:

• Access to all data regardless of source or type
• Flexibility to support changing workloads and consumption cases
• Intelligent analytics, such as machine learning, that can run at the source of data
• Access to insights across the business, its functions, and to all users for better decision making

Solutions you may consider to drive improvements include:

• IBM Db2 family

Modernize

Your Responses Peer Comparison

Make your data ready for an AI and hybrid cloud world. Indicate your current capabilities and maturity, and see your score / compare to your peers.

None

(0)

Ad-hoc

(1)

Standardized

(2)

Actively Managed

(3)

Optimizing

(4)

N/A

(5)

Have you adopted cloud-native architecture to deploy analytics services both on premises and on any cloud?

None

Ad-hoc

Standardized

Actively
Managed

Optimizing

N/A

Your Organization

Your peer average

None

(0)

Ad-hoc

(1)

Standardized

(2)

Actively Managed

(3)

Optimizing

(4)

N/A

(5)

Have you adopted cloud-native architecture to deploy analytics services both on premises and on any cloud?

Modernize

What is meant by "modernize"? Modernize means building an information architecture for AI that provides choice and flexibility across your enterprise.

As you modernize for an AI and multicloud world, as you modernize you will find that there is less "assembly required" in expanding the impact of AI across the organization.

Your Organization

Your Peers

Compared to  of your peers in the  industry

To help address these challenges you should:

• Deploy an information architecture for AI
• Prepare data for a multicloud world
• Infuse AI everywhere, with confidence
• Harness the flexibility and growth of open source technologies
• Speed time-to-value with unprecedented simplicity & agility

Solutions you may consider to drive improvements include:

• IBM Cloud Pak for Data
• IBM Cloud Pak for Data Systems

The Value of Advancing Your Journey to AI

Improving your journey to AI can help drive value in your organization. The default values provided are based on independent review as top the value of AI journey improvements. Adjust the values and review the assumptions to personalize the analysis to match your unique value potential from streamlining your AI journey.

Progress on Your AI Journey

Your Organization

Your Peers

Compared to  of your peers in the
 industry

Recommendations for You

• Implement an open, extensible information architecture for AI
• Establish ONE unified set of cloud-native data & AI services, on any cloud
• Automate the end-to-end data and AI lifecycle management
• Virtualize all data, regardless of where it lives
• Integrate and govern data across hybrid cloud and data settings
• Dynamically scale on-demand to accommodate changing needs

Potential Annual Value of Advancing Your Journey to AI

Productivity improvement(Data Engineer, Data Stewards, Administrators) Productivity improvement (Data Scientists) Probability of regulatory risk event Probability of reputational risk event Improvement of time-to-value Improvement due to increased trust in AI

Reduce Cost

Reduce Risks

Increase Revenue

Edit Assumptions »

Expected Benefits

enter investment

The expected cost savings and risk avoidance expected from Company XYZ

Expected five year benefits

Average annual benefit

Benefits by year

Business Value Analysis

edit investment

The Company XYZ Platform: Projected payback period and rate of return

Initial

Year 1

Year 2

Year 3

Expected benefits

Initial

Year 1

Year 2

Year 3

Cumulative expected benefits

Initial

Year 1

Year 2

Year 3

Planned investment

Initial

Year 1

Year 2

Year 3

Cumulative investment

Initial

Year 1

Year 2

Year 3

Net improvement

Initial

Year 1

Year 2

Year 3

Cumulative net improvement

Initial

Year 1

Year 2

Year 3

ROI

  months

Payback period

NPV savings

Cumulative investments vs benefits

Next Steps

Get your personalized report

Get Report Get Report

Learn about success from organizations just like yours

Speed digital transformation by digesting and unifying volumes of data for real-time AI insights delivered as cloud AI microservices

Explore »

Collect data across complex, disparate sources while employing AI models for data and customer protection

Explore »

Real-time, predictive criminal risk profiling using business-ready data cataloged from 40M+ records, 200M court cases, social media, etc.

Explore »

View More »