What is involved in Prescriptive Analytics

Find out what the related areas are that Prescriptive Analytics connects with, associates with, correlates with or affects, and which require thought, deliberation, analysis, review and discussion. This unique checklist stands out in a sense that it is not per-se designed to give answers, but to engage the reader and lay out a Prescriptive Analytics thinking-frame.

How far is your company on its Prescriptive Analytics journey?

Take this short survey to gauge your organization’s progress toward Prescriptive Analytics leadership. Learn your strongest and weakest areas, and what you can do now to create a strategy that delivers results.

To address the criteria in this checklist for your organization, extensive selected resources are provided for sources of further research and information.

Start the Checklist

Below you will find a quick checklist designed to help you think about which Prescriptive Analytics related domains to cover and 134 essential critical questions to check off in that domain.

The following domains are covered:

Prescriptive Analytics, Applied statistics, Big data, Business analytics, Business intelligence, Business operations, Business process, Computational model, Computational science, Data mining, Decision Engineering, Decision Management, Health, Safety and Environment, Health care in the United States, Health care provider, Map reduce, Mathematical model, Mathematical sciences, Natural gas prices, Operations research, Predictive analytics, Structured data, Unstructured data, Utility companies:

Prescriptive Analytics Critical Criteria:

Track Prescriptive Analytics issues and don’t overlook the obvious.

– Can we add value to the current Prescriptive Analytics decision-making process (largely qualitative) by incorporating uncertainty modeling (more quantitative)?

– What is the total cost related to deploying Prescriptive Analytics, including any consulting or professional services?

– Who needs to know about Prescriptive Analytics ?

Applied statistics Critical Criteria:

Check Applied statistics leadership and probe the present value of growth of Applied statistics.

– Who will be responsible for documenting the Prescriptive Analytics requirements in detail?

– Will Prescriptive Analytics deliverables need to be tested and, if so, by whom?

– Is Supporting Prescriptive Analytics documentation required?

Big data Critical Criteria:

Track Big data tasks and ask what if.

– If this nomination is completed on behalf of the customer, has that customer been made aware of this nomination in advance of this submission?

– Erp versus big data are the two philosophies of information architecture consistent complementary or in conflict with each other?

– Looking at hadoop big data in the rearview mirror what would you have done differently after implementing a Data Lake?

– What is (or would be) the added value of collaborating with other entities regarding data sharing in your sector?

– To what extent does your organization have experience with big data and data-driven innovation (DDI)?

– The real challenge: are you willing to get better value and more innovation for some loss of privacy?

– Which departments in your organization are involved in using data technologies and data analytics?

– Does big data threaten the traditional data warehouse business intelligence model stack?

– Which core Oracle Business Intelligence or Big Data Analytics products are used in your solution?

– Does our entire organization have easy access to information required to support work processes?

– What would be needed to support collaboration on data sharing across economic sectors?

– Which other Oracle Business Intelligence products are used in your solution?

– Does your organization have the necessary skills to handle big data?

– How do you handle Big Data in Analytic Applications?

– What are our tools for big data analytics?

– Which Oracle applications are used in your project?

– What metrics do we use to assess the results?

– What if the data cannot fit on your computer?

– Where Is This Big Data Coming From ?

– How to use in practice?

Business analytics Critical Criteria:

Closely inspect Business analytics projects and document what potential Business analytics megatrends could make our business model obsolete.

– Marketing budgets are tighter, consumers are more skeptical, and social media has changed forever the way we talk about Prescriptive Analytics. How do we gain traction?

– How do senior leaders actions reflect a commitment to the organizations Prescriptive Analytics values?

– what is the most effective tool for Statistical Analysis Business Analytics and Business Intelligence?

– How likely is the current Prescriptive Analytics plan to come in on schedule or on budget?

– What is the difference between business intelligence business analytics and data mining?

– Is there a mechanism to leverage information for business analytics and optimization?

– What is the difference between business intelligence and business analytics?

– what is the difference between Data analytics and Business Analytics If Any?

– How do you pick an appropriate ETL tool or business analytics tool?

– What are the trends shaping the future of business analytics?

Business intelligence Critical Criteria:

Guard Business intelligence decisions and simulate teachings and consultations on quality process improvement of Business intelligence.

– Does the software let users work with the existing data infrastructure already in place, freeing your IT team from creating more cubes, universes, and standalone marts?

– As we develop increasing numbers of predictive models, then we have to figure out how do you pick the targets, how do you optimize the models?

– Does your software provide roleand group-based security options that allow business users to securely create and publish their work?

– Does creating or modifying reports or dashboards require a reporting team?

– Does your BI solution help you find the right views to examine your data?

– What are the best UI frameworks for Business Intelligence Applications?

– Is data warehouseing necessary for our business intelligence service?

– Can your bi solution quickly locate dashboard on your mobile device?

– What are the main full web business intelligence solutions?

– What type and complexity of system administration roles?

– How do we use AI algorithms in practical applications?

– What are the best client side analytics tools today?

– Is your software easy for IT to manage and upgrade?

– What is the future of BI Score cards KPI etc?

– How is business intelligence disseminated?

– How can we maximize our BI investments?

– Is your BI software easy to understand?

– Using dashboard functions?

– Why BI?

Business operations Critical Criteria:

Confer re Business operations goals and get the big picture.

– Is legal review performed on all intellectual property utilized in the course of your business operations?

– How to move the data in legacy systems to the cloud environment without interrupting business operations?

– What are the Essentials of Internal Prescriptive Analytics Management?

– How would one define Prescriptive Analytics leadership?

– Is the scope of Prescriptive Analytics defined?

Business process Critical Criteria:

Probe Business process management and devise Business process key steps.

– Have the segments, goals and performance objectives been translated into an actionable and realistic target business and information architecture expressed within business functions, business processes, and information requirements?

– To what extent will this product open up for subsequent add-on products, e.g. business process outsourcing services built on top of a program-as-a-service offering?

– What is the importance of knowing the key performance indicators KPIs for a business process when trying to implement a business intelligence system?

– Has business process Cybersecurity has been included in continuity of operations plans for areas such as customer data, billing, etc.?

– Are interruptions to business activities counteracted and critical business processes protected from the effects of major failures or disasters?

– When conducting a business process reengineering study, what should we look for when trying to identify business processes to change?

– What are the disruptive Prescriptive Analytics technologies that enable our organization to radically change our business processes?

– If we process purchase orders; what is the desired business process around supporting purchase orders?

– If we accept wire transfers what is the desired business process around supporting wire transfers?

– How do clients contact client services with any questions about business processes?

– If we accept checks what is the desired business process around supporting checks?

– What are the relationships with other business processes and are these necessary?

– How do you inventory and assess business processes as part of an ERP evaluation?

– What would Eligible entity be asked to do to facilitate your normal business process?

– What are the usability implications of Prescriptive Analytics actions?

– How will business process and behavioral change be managed?

– What is the business process?

Computational model Critical Criteria:

Map Computational model tasks and test out new things.

– How do we keep improving Prescriptive Analytics?

Computational science Critical Criteria:

Powwow over Computational science strategies and question.

– What is the source of the strategies for Prescriptive Analytics strengthening and reform?

– Do we have past Prescriptive Analytics Successes?

Data mining Critical Criteria:

Think carefully about Data mining goals and research ways can we become the Data mining company that would put us out of business.

– Record-keeping requirements flow from the records needed as inputs, outputs, controls and for transformation of a Prescriptive Analytics process. ask yourself: are the records needed as inputs to the Prescriptive Analytics process available?

– Do you see the need to clarify copyright aspects of the data-driven innovation (e.g. with respect to technologies such as text and data mining)?

– What types of transactional activities and data mining are being used and where do we see the greatest potential benefits?

– What is the difference between Data Analytics Data Analysis Data Mining and Data Science?

– Is business intelligence set to play a key role in the future of Human Resources?

– Why is Prescriptive Analytics important for you now?

– What programs do we have to teach data mining?

– How to Secure Prescriptive Analytics?

Decision Engineering Critical Criteria:

Reconstruct Decision Engineering adoptions and correct better engagement with Decision Engineering results.

– How do we manage Prescriptive Analytics Knowledge Management (KM)?

Decision Management Critical Criteria:

Jump start Decision Management risks and explain and analyze the challenges of Decision Management.

– What are the success criteria that will indicate that Prescriptive Analytics objectives have been met and the benefits delivered?

– How can skill-level changes improve Prescriptive Analytics?

Health, Safety and Environment Critical Criteria:

Collaborate on Health, Safety and Environment decisions and improve Health, Safety and Environment service perception.

– What are the Key enablers to make this Prescriptive Analytics move?

– What threat is Prescriptive Analytics addressing?

Health care in the United States Critical Criteria:

Sort Health care in the United States tasks and oversee implementation of Health care in the United States.

– A compounding model resolution with available relevant data can often provide insight towards a solution methodology; which Prescriptive Analytics models, tools and techniques are necessary?

– Risk factors: what are the characteristics of Prescriptive Analytics that make it risky?

– Are there Prescriptive Analytics problems defined?

Health care provider Critical Criteria:

Inquire about Health care provider outcomes and clarify ways to gain access to competitive Health care provider services.

– How will we insure seamless interoperability of Prescriptive Analytics moving forward?

– Have all basic functions of Prescriptive Analytics been defined?

– What are the long-term Prescriptive Analytics goals?

Map reduce Critical Criteria:

Tête-à-tête about Map reduce failures and devote time assessing Map reduce and its risk.

– How can you negotiate Prescriptive Analytics successfully with a stubborn boss, an irate client, or a deceitful coworker?

– When a Prescriptive Analytics manager recognizes a problem, what options are available?

– Are there recognized Prescriptive Analytics problems?

Mathematical model Critical Criteria:

Pilot Mathematical model tactics and change contexts.

– Well-defined, appropriate concepts of the technology are in widespread use, the technology may have been in use for many years, a formal mathematical model is defined, etc.)?

– Think of your Prescriptive Analytics project. what are the main functions?

– Why should we adopt a Prescriptive Analytics framework?

Mathematical sciences Critical Criteria:

Do a round table on Mathematical sciences goals and catalog Mathematical sciences activities.

– What may be the consequences for the performance of an organization if all stakeholders are not consulted regarding Prescriptive Analytics?

– Who will be responsible for deciding whether Prescriptive Analytics goes ahead or not after the initial investigations?

– In a project to restructure Prescriptive Analytics outcomes, which stakeholders would you involve?

Natural gas prices Critical Criteria:

Guard Natural gas prices visions and describe the risks of Natural gas prices sustainability.

– How do your measurements capture actionable Prescriptive Analytics information for use in exceeding your customers expectations and securing your customers engagement?

– Who is the main stakeholder, with ultimate responsibility for driving Prescriptive Analytics forward?

– Is Prescriptive Analytics Realistic, or are you setting yourself up for failure?

Operations research Critical Criteria:

Chat re Operations research risks and research ways can we become the Operations research company that would put us out of business.

– Do those selected for the Prescriptive Analytics team have a good general understanding of what Prescriptive Analytics is all about?

– What are the barriers to increased Prescriptive Analytics production?

Predictive analytics Critical Criteria:

Consider Predictive analytics risks and probe Predictive analytics strategic alliances.

– What are our best practices for minimizing Prescriptive Analytics project risk, while demonstrating incremental value and quick wins throughout the Prescriptive Analytics project lifecycle?

– What are your most important goals for the strategic Prescriptive Analytics objectives?

– What are direct examples that show predictive analytics to be highly reliable?

– How do we Identify specific Prescriptive Analytics investment and emerging trends?

Structured data Critical Criteria:

Gauge Structured data leadership and forecast involvement of future Structured data projects in development.

– Do we aggressively reward and promote the people who have the biggest impact on creating excellent Prescriptive Analytics services/products?

– What tools do you consider particularly important to handle unstructured data expressed in (a) natural language(s)?

– Does your organization have the right tools to handle unstructured data expressed in (a) natural language(s)?

– Should you use a hierarchy or would a more structured database-model work best?

– What is our Prescriptive Analytics Strategy?

Unstructured data Critical Criteria:

Weigh in on Unstructured data tasks and point out Unstructured data tensions in leadership.

– Does the Prescriptive Analytics task fit the clients priorities?

Utility companies Critical Criteria:

Frame Utility companies governance and test out new things.

– Have you identified your Prescriptive Analytics key performance indicators?

– How do we Improve Prescriptive Analytics service perception, and satisfaction?


This quick readiness checklist is a selected resource to help you move forward. Learn more about how to achieve comprehensive insights with the Prescriptive Analytics Self Assessment:


Author: Gerard Blokdijk

CEO at The Art of Service | theartofservice.com

[email protected]


Gerard is the CEO at The Art of Service. He has been providing information technology insights, talks, tools and products to organizations in a wide range of industries for over 25 years. Gerard is a widely recognized and respected information expert. Gerard founded The Art of Service consulting business in 2000. Gerard has authored numerous published books to date.

External links:

To address the criteria in this checklist, these selected resources are provided for sources of further research and information:

Prescriptive Analytics External links:

Prescriptive Analytics – Gartner IT Glossary

How to Get Started With Prescriptive Analytics

Big data External links:

Qognify: Big Data Solutions for Physical Security & …

Pepperdata: DevOps for Big Data

Business analytics External links:

Power BI Business Analytics Solutions

Business intelligence External links:

business intelligence jobs | Dice.com

[PDF]Position Title: Business Intelligence Analyst – ttra

Business operations External links:

UofL Business Operations

How much does a business operations manager make?

Business process External links:

Business Process Improvement Jobs – Monster.com

What is business process? – Definition from WhatIs.com

Business Process Analyst Jobs, Employment | Indeed.com

Computational model External links:

Title: A computational model of affects – arXiv

Computational Model. (Conference) | SciTech Connect

CiteSeerX — Computational Model

Computational science External links:

Computational Science – UTEP

Computational science (Book, 2007) [WorldCat.org]

Computational science (eBook, 2007) [WorldCat.org]

Data mining External links:

Title Data Mining Jobs, Employment | Indeed.com

[PDF]Project Title: Data Mining to Improve Water Management

data aggregation in data mining ppt

Decision Engineering External links:

Decision engineering – encyclopedia article – Citizendium

Decision Management External links:

Decision Management – SourceWatch

MSDN Software – Computer Information and Decision Management

Health, Safety and Environment External links:

HSE Talk | Health, Safety and Environment discussions

Health, Safety and Environment Policies – Search

Health, Safety and Environment (HSE) Practices – Anadarko

Health care provider External links:

Mutual of Omaha’s Health Care Provider Access – Contact Us

About Us | Wilmington Health Care Provider

Cigna Health Care Provider Directory

Map reduce External links:

Map Reduce Flashcards | Quizlet

Top 20 Hadoop and Map Reduce Interview Questions – …

4.0 Nested map reduce – Google Groups

Mathematical model External links:

“Mathematical Model for Current Transformer Based On …

[1009.1031] A mathematical model of the Mafia game – arXiv

Mathematical Model Cont Mech 2ed. (eBook, 2005) …

Mathematical sciences External links:

Conference Board of the Mathematical Sciences

Department of Mathematical Sciences

Mathematical Sciences | University of Arkansas

Natural gas prices External links:

Compare Natural Gas Prices and Cost in Pennsylvania: UGI

Will Mild Weather Impact Natural Gas Prices? – Market …

Ohio Natural Gas Prices | Gas Supplier | Shipley Energy

Operations research External links:

Operations Research on JSTOR

Systems Engineering and Operations Research

Operations Research Analysis Manager Salaries – Salary.com

Predictive analytics External links:

Predictive Analytics Workers Compensation

Best Predictive Analytics Software in 2017 | G2 Crowd

Predictive Analytics Software, Social Listening | NewBrand

Structured data External links:

How to Add Structured Data to Your Website – Neil Patel

[PDF]Efficient Population of Structured Data Forms for …

n4e Ltd Structured Data cabling | Electrical Installations

Utility companies External links:

City of Buena Park, CA : Utility Companies

V.A.F. Industries | Products for Utility Companies

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