131 Prescriptive Analytics Criteria for Multi-purpose Projects

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 131 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:

Facilitate Prescriptive Analytics failures and clarify ways to gain access to competitive Prescriptive Analytics services.

– What are all of our Prescriptive Analytics domains and what do they do?

– Can we do Prescriptive Analytics without complex (expensive) analysis?

Applied statistics Critical Criteria:

Reconstruct Applied statistics goals and spearhead techniques for implementing Applied statistics.

– Who will be responsible for making the decisions to include or exclude requested changes once Prescriptive Analytics is underway?

– Is the Prescriptive Analytics organization completing tasks effectively and efficiently?

– What are our Prescriptive Analytics Processes?

Big data Critical Criteria:

Examine Big data issues and prioritize challenges of Big data.

– New roles. Executives interested in leading a big data transition can start with two simple techniques. First, they can get in the habit of asking What do the data say?

– How we make effective use of the flood of data that will be produced will be a real big data challenge: should we keep it all or could we throw some away?

– Do we address the daunting challenge of Big Data: how to make an easy use of highly diverse data and provide knowledge?

– What is (or would be) the added value of collaborating with other entities regarding data sharing across economic sectors?

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

– How should we organize to capture the benefit of Big Data and move swiftly to higher maturity stages?

– What are the ways in which cloud computing and big data can work together?

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

– What are the new applications that are enabled by Big Data solutions?

– What analytical tools do you consider particularly important?

– What is it that we don t know we don t know about the data?

– What is tacit permission and approval, anyway?

– What is the cost of partitioning/balancing?

– Wait, DevOps does not apply to Big Data?

– What are some impacts of Big Data?

– what is Different about Big Data?

– Find traffic bottlenecks ?

– What is Big Data to us?

– What are we missing?

Business analytics Critical Criteria:

Troubleshoot Business analytics failures and handle a jump-start course to Business analytics.

– What are the key elements of your Prescriptive Analytics performance improvement system, including your evaluation, organizational learning, and innovation processes?

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

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

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

– Are we making progress? and are we making progress as Prescriptive Analytics leaders?

– What are the record-keeping requirements of Prescriptive Analytics activities?

– 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:

Ventilate your thoughts about Business intelligence outcomes and probe Business intelligence strategic alliances.

– What information can be provided in regards to a sites usage and business intelligence usage within the intranet environment?

– Does your bi solution require weeks of training before new users can analyze data and publish dashboards?

– Does your bi software work well with both centralized and decentralized data architectures and vendors?

– Can you filter, drill down, or add entirely new data to your visualization with mobile editing?

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

– Does your BI solution allow analytical insights to happen anywhere and everywhere?

– Is business intelligence set to play a key role in the future of human resources?

– What documentation is provided with the software / system and in what format?

– What tools are there for publishing sharing and visualizing data online?

– What information needs of managers are satisfied by the bi system?

– What are the pros and cons of outsourcing Business Intelligence?

– Number of data sources that can be simultaneously accessed?

– Can users easily create these thresholds and alerts?

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

– How stable is it across domains/geographies?

– Will your product work from a mobile device?

– Describe any training materials offered?

– Is your BI software easy to understand?

– Using dashboard functions?

Business operations Critical Criteria:

Differentiate Business operations engagements and oversee Business operations requirements.

– 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?

– How do we know that any Prescriptive Analytics analysis is complete and comprehensive?

– Does Prescriptive Analytics analysis isolate the fundamental causes of problems?

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

Business process Critical Criteria:

Merge Business process engagements and gather practices for scaling Business process.

– Do we identify maximum allowable downtime for critical business functions, acceptable levels of data loss and backlogged transactions, RTOs, RPOs, recovery of the critical path (i.e., business processes or systems that should receive the highest priority), and the costs associated with downtime? Are the approved thresholds appropriate?

– 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.?

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

– Do we have detailed information on the business process for refunds and charge backs if they are required?

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

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

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

– Do changes in business processes fall under the scope of Change Management?

– What business process supports the entry and validation of the data?

– How do we improve business processes and how do we deliver on that?

– What core business processes drive our industry and channel today?

– How does the solution handle core business processes?

– What/how are business processes defined?

– What is the business process?

Computational model Critical Criteria:

Exchange ideas about Computational model results and pay attention to the small things.

– What tools and technologies are needed for a custom Prescriptive Analytics project?

– What are the long-term Prescriptive Analytics goals?

Computational science Critical Criteria:

Devise Computational science quality and display thorough understanding of the Computational science process.

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

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

Data mining Critical Criteria:

Adapt Data mining visions and look at the big picture.

– 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?

– Are there any disadvantages to implementing Prescriptive Analytics? There might be some that are less obvious?

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

– What programs do we have to teach data mining?

– Is a Prescriptive Analytics Team Work effort in place?

– What is our Prescriptive Analytics Strategy?

Decision Engineering Critical Criteria:

Experiment with Decision Engineering goals and change contexts.

– What are your results for key measures or indicators of the accomplishment of your Prescriptive Analytics strategy and action plans, including building and strengthening core competencies?

– 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?

– Think about the functions involved in your Prescriptive Analytics project. what processes flow from these functions?

Decision Management Critical Criteria:

Familiarize yourself with Decision Management quality and achieve a single Decision Management view and bringing data together.

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

– Do we have past Prescriptive Analytics Successes?

– How much does Prescriptive Analytics help?

Health, Safety and Environment Critical Criteria:

Administer Health, Safety and Environment results and probe Health, Safety and Environment strategic alliances.

– Which individuals, teams or departments will be involved in Prescriptive Analytics?

– Are accountability and ownership for Prescriptive Analytics clearly defined?

Health care in the United States Critical Criteria:

Canvass Health care in the United States engagements and don’t overlook the obvious.

– What prevents me from making the changes I know will make me a more effective Prescriptive Analytics leader?

– Do we monitor the Prescriptive Analytics decisions made and fine tune them as they evolve?

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

Health care provider Critical Criteria:

Nurse Health care provider issues and probe using an integrated framework to make sure Health care provider is getting what it needs.

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

Map reduce Critical Criteria:

Facilitate Map reduce tactics and handle a jump-start course to Map reduce.

– Does Prescriptive Analytics analysis show the relationships among important Prescriptive Analytics factors?

– Is maximizing Prescriptive Analytics protection the same as minimizing Prescriptive Analytics loss?

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

Mathematical model Critical Criteria:

Jump start Mathematical model engagements and overcome Mathematical model skills and management ineffectiveness.

– 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.)?

– What other organizational variables, such as reward systems or communication systems, affect the performance of this Prescriptive Analytics process?

– Will Prescriptive Analytics have an impact on current business continuity, disaster recovery processes and/or infrastructure?

– How to deal with Prescriptive Analytics Changes?

Mathematical sciences Critical Criteria:

Check Mathematical sciences projects and learn.

– What will be the consequences to the business (financial, reputation etc) if Prescriptive Analytics does not go ahead or fails to deliver the objectives?

– Have you identified your Prescriptive Analytics key performance indicators?

– What threat is Prescriptive Analytics addressing?

Natural gas prices Critical Criteria:

Steer Natural gas prices outcomes and tour deciding if Natural gas prices progress is made.

– How can we incorporate support to ensure safe and effective use of Prescriptive Analytics into the services that we provide?

– Does the Prescriptive Analytics task fit the clients priorities?

Operations research Critical Criteria:

Rank Operations research goals and don’t overlook the obvious.

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

Predictive analytics Critical Criteria:

Substantiate Predictive analytics planning and create a map for yourself.

– What are your key performance measures or indicators and in-process measures for the control and improvement of your Prescriptive Analytics processes?

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

– What are specific Prescriptive Analytics Rules to follow?

– Who sets the Prescriptive Analytics standards?

Structured data Critical Criteria:

Coach on Structured data leadership and interpret which customers can’t participate in Structured data because they lack skills.

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

– How does the organization define, manage, and improve its Prescriptive Analytics processes?

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

– How do we go about Securing Prescriptive Analytics?

Unstructured data Critical Criteria:

Interpolate Unstructured data visions and correct better engagement with Unstructured data results.

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

– Who needs to know about Prescriptive Analytics ?

Utility companies Critical Criteria:

Sort Utility companies quality and triple focus on important concepts of Utility companies relationship management.

– What is the purpose of Prescriptive Analytics in relation to the mission?


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



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 Definition | Cornerstone AU Glossary

Healthcare Prescriptive Analytics – Cedar Gate Technologies

How to Get Started With Prescriptive Analytics

Applied statistics External links:

Applied statistics (Book, 1978) [WorldCat.org]

Master of Applied Statistics – ANU – Programs and Courses

Master of Applied Statistics (Online) | Statistics

Big data External links:

Loudr: Big Data for Music Rights

UpX Academy – Master Big Data & Data Science online

Big Data Big Heart Hackathon 2017 | A CloudTrek Initiative

Business analytics External links:

ABA | Accounting + Business Analytics

Expense Management & Business Analytics | Smartbill

MODLR — Adaptive and Collaborative Business Analytics

Business intelligence External links:

Online market research, business intelligence, data analytics

Ruralco | Business Intelligence

ORC International | Leading Global Business Intelligence Firm

Business operations External links:

Wrike – Business Operations Management

Business Operations – P&Cs Qld

What is Business Operations – Answers.com

Business process External links:

Business Process Outsourcing Australia | Sitel

Business Process Outsourcing (BPO) Company – NTC VOICE

Business Process & Document Automation Software – Esker

Computational model External links:


The face-space duality hypothesis: a computational model

A Computational Model of Music Composition – DASH Harvard

Computational science External links:

Computational Science and Engineering Education Program

ICCS – International Conference on Computational Science

UM Center for computational Science brochure – issuu

Data mining External links:

Data Analysis Australia: Data Mining – daa.com.au

Project Title: Data Mining to Improve Water Management

data aggregation in data mining ppt

Decision Engineering External links:

Decision Engineering Corporation – deceng.net

Decision Engineering – Springer

Integrated Decision Engineering Analysis, Inc.

Decision Management External links:

Decision Management System DMS – Landmark Solutions

Decision Management Defined – cleverism.com

Avola Decision | Decision Management and Automation

Health, Safety and Environment External links:

Health, Safety and Environment | InvoCare

Impact Fertilisers : Health, Safety and Environment Policy

Epic Energy – Health, Safety and Environment

Health care provider External links:

What Is a Health Care Provider? – Verywell

Health Care Provider – Mrs Peggs Handy Line Clotheslines

Select a Health Care Provider from our Portal | Bankers Life

Map reduce External links:

Phoenix Map Reduce | Apache Phoenix

CC-Bill-Tracker – These map reduce functions use Common Crawl data to look at the spread of congressional legislation on the internet
Data Vault 2.0 and Hadoop Map/Reduce

Map Reduce: A really simple introduction – Kaushik Sathupadi

Mathematical model External links:

How to Make a Mathematical Model: 9 Steps (with Pictures)

Mathematical model – ScienceDaily

Mathematical sciences External links:

ANU – Mathematical Sciences Institute – Ben Andrews

Master of Science (Mathematical Sciences): Curtin University

Research in the Mathematical Sciences | Home

Natural gas prices External links:

Where Natural Gas Prices Could Go Next Week – Market Realist

Natural Gas Prices – Gas Price Chart, Forecast & Analysis

Natural gas prices have reached a turning point – Atradius

Operations research External links:

Course Syllabus Course Title: Operations Research

RAIRO – Operations Research

Montreal Operations Research Student Chapter MORSC | Home

Predictive analytics External links:

Predictive Analytics & Big Data

Predictive Analytics | NICE

Predictive Analytics by Page – issuu

Structured data External links:

eBay Seller Centre – Structured data 2016 | eBay Seller Centre

How to Add Structured Data to Your Website – Neil Patel

Introduction to Structured Data | Search | Google Developers

Unstructured data External links:

Protection of unstructured data – Capgemini

Illuminate your unstructured data | IDM Magazine

Unstructured data – GovHack Hackathon

Utility companies External links:

Live Twitter Feeds – Utility Companies

SolarCity vs. the utility companies – YouTube

Utility Companies Power Up To Recruit Top Management – WSJ