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 126 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:
Accelerate Prescriptive Analytics adoptions and customize techniques for implementing Prescriptive Analytics controls.
– Who is responsible for ensuring appropriate resources (time, people and money) are allocated to Prescriptive Analytics?
– Does Prescriptive Analytics systematically track and analyze outcomes for accountability and quality improvement?
– Are accountability and ownership for Prescriptive Analytics clearly defined?
Applied statistics Critical Criteria:
Consolidate Applied statistics engagements and ask what if.
– What tools do you use once you have decided on a Prescriptive Analytics strategy and more importantly how do you choose?
– Among the Prescriptive Analytics product and service cost to be estimated, which is considered hardest to estimate?
– What are the barriers to increased Prescriptive Analytics production?
Big data Critical Criteria:
Conceptualize Big data adoptions and question.
– Do you see the need to address the issues of data ownership or access to non-personal data (e.g. machine-generated data)?
– To what extent does your organization have experience with big data and data-driven innovation (DDI)?
– Which departments in your organization are involved in using data technologies and data analytics?
– What are the disruptive innovations in the middle-term that provide near-term domain leadership?
– Wheres the evidence that using big data intelligently will improve business performance?
– Technology Drivers – What were the primary technical challenges your organization faced?
– How does big data impact Data Quality and governance best practices?
– How can the best Big Data solution be chosen based on use case requirements?
– Which other Oracle Business Intelligence products are used in your solution?
– How will systems and methods evolve to remove Big Data solution weaknesses?
– Does your organization have a strategy on big data or data analytics?
– When we plan and design, how well do we capture previous experience?
– With more data to analyze, can Big Data improve decision-making?
– Where do you see the need for standardisation actions?
– How does that compare to other science disciplines?
– what is Different about Big Data?
– Does Big Data Really Need HPC?
– How to deal with ambiguity?
– How much data so far?
Business analytics Critical Criteria:
Grasp Business analytics strategies and pay attention to the small things.
– Are there any easy-to-implement alternatives to Prescriptive Analytics? Sometimes other solutions are available that do not require the cost implications of a full-blown project?
– 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?
– 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?
– What threat is Prescriptive Analytics addressing?
– What is our Prescriptive Analytics Strategy?
Business intelligence Critical Criteria:
Confer over Business intelligence issues and devote time assessing Business intelligence and its risk.
– Does your bi solution require weeks of training before new users can analyze data and publish dashboards?
– What strategies will we pursue to ensure the success of the business intelligence competency center?
– Which core Oracle Business Intelligence or Big Data Analytics products are used in your solution?
– Is business intelligence set to play a key role in the future of human resources?
– What are the best BI and reporting tools for embedding in a SaaS application?
– Does creating or modifying reports or dashboards require a reporting team?
– What is the process of data transformation required by your system?
– Is Data Warehouseing necessary for a business intelligence service?
– What are the pros and cons of outsourcing Business Intelligence?
– Are there any on demand analytics tools in the cloud?
– Is your software easy for it to manage and upgrade?
– How is business intelligence disseminated?
– Is your BI software easy to understand?
– Do you offer formal user training?
– What is your annual maintenance?
– What is your products direction?
– How to Secure Prescriptive Analytics?
Business operations Critical Criteria:
Give examples of Business operations visions and know what your objective is.
– 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?
– Who is the main stakeholder, with ultimate responsibility for driving Prescriptive Analytics forward?
– Does Prescriptive Analytics analysis isolate the fundamental causes of problems?
Business process Critical Criteria:
Exchange ideas about Business process projects and observe effective 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?
– 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?
– What are the disruptive Prescriptive Analytics technologies that enable our organization to radically change our business processes?
– Do you design data protection and privacy requirements into the development of your business processes and new systems?
– What finance, procurement and Human Resources business processes should be included in the scope of a erp solution?
– Do the functional areas need business process integration (e.g., order entl. billing, or Customer Service)?
– Do we have detailed information on the business process for refunds and charge backs if they are required?
– To satisfy customers and stakeholders, which internal business process must we excel in?
– Is the Prescriptive Analytics organization completing tasks effectively and efficiently?
– If we accept checks what is the desired business process around supporting checks?
– Will existing staff require re-training, for example, to learn new business processes?
– What would Eligible entity be asked to do to facilitate your normal business process?
– What business process supports the entry and validation of the data?
Computational model Critical Criteria:
Discourse Computational model engagements and define Computational model competency-based leadership.
– What are your most important goals for the strategic Prescriptive Analytics objectives?
– What are the long-term Prescriptive Analytics goals?
– Are there recognized Prescriptive Analytics problems?
Computational science Critical Criteria:
Have a session on Computational science projects and tour deciding if Computational science progress is made.
– Is maximizing Prescriptive Analytics protection the same as minimizing Prescriptive Analytics loss?
– How do we manage Prescriptive Analytics Knowledge Management (KM)?
Data mining Critical Criteria:
Distinguish Data mining projects and budget for Data mining challenges.
– 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 total cost related to deploying Prescriptive Analytics, including any consulting or professional services?
– What is the difference between Data Analytics Data Analysis Data Mining and Data Science?
– What business benefits will Prescriptive Analytics goals deliver if achieved?
– What programs do we have to teach data mining?
Decision Engineering Critical Criteria:
Have a meeting on Decision Engineering results and report on setting up Decision Engineering without losing ground.
– Why is Prescriptive Analytics important for you now?
– Are there Prescriptive Analytics problems defined?
– What are our Prescriptive Analytics Processes?
Decision Management Critical Criteria:
Understand Decision Management outcomes and budget for Decision Management challenges.
– How do we know that any Prescriptive Analytics analysis is complete and comprehensive?
– What are all of our Prescriptive Analytics domains and what do they do?
– Why should we adopt a Prescriptive Analytics framework?
Health, Safety and Environment Critical Criteria:
Be clear about Health, Safety and Environment issues and summarize a clear Health, Safety and Environment focus.
– Is there any existing Prescriptive Analytics governance structure?
– Is Supporting Prescriptive Analytics documentation required?
Health care in the United States Critical Criteria:
Align Health care in the United States projects and be persistent.
– What are the success criteria that will indicate that Prescriptive Analytics objectives have been met and the benefits delivered?
– Is Prescriptive Analytics Realistic, or are you setting yourself up for failure?
Health care provider Critical Criteria:
Differentiate Health care provider tactics and explain and analyze the challenges of Health care provider.
– How will you know that the Prescriptive Analytics project has been successful?
– What about Prescriptive Analytics Analysis of results?
Map reduce Critical Criteria:
Mine Map reduce tasks and probe the present value of growth of Map reduce.
– Who will be responsible for documenting the Prescriptive Analytics requirements in detail?
– How can the value of Prescriptive Analytics be defined?
Mathematical model Critical Criteria:
Deduce Mathematical model tasks and assess what counts with Mathematical model that we are not counting.
– 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 will be the consequences to the business (financial, reputation etc) if Prescriptive Analytics does not go ahead or fails to deliver the objectives?
– How do we ensure that implementations of Prescriptive Analytics products are done in a way that ensures safety?
– Which Prescriptive Analytics goals are the most important?
Mathematical sciences Critical Criteria:
Wrangle Mathematical sciences tactics and find out what it really means.
– Why is it important to have senior management support for a Prescriptive Analytics project?
– Do Prescriptive Analytics rules make a reasonable demand on a users capabilities?
Natural gas prices Critical Criteria:
Tête-à-tête about Natural gas prices governance and budget the knowledge transfer for any interested in Natural gas prices.
– Can we do Prescriptive Analytics without complex (expensive) analysis?
– Does our organization need more Prescriptive Analytics education?
– Are there Prescriptive Analytics Models?
Operations research Critical Criteria:
Incorporate Operations research leadership and gather practices for scaling Operations research.
– Do we aggressively reward and promote the people who have the biggest impact on creating excellent Prescriptive Analytics services/products?
– What are the top 3 things at the forefront of our Prescriptive Analytics agendas for the next 3 years?
Predictive analytics Critical Criteria:
Transcribe Predictive analytics goals and probe Predictive analytics strategic alliances.
– Consider your own Prescriptive Analytics project. what types of organizational problems do you think might be causing or affecting your problem, based on the work done so far?
– What are the key elements of your Prescriptive Analytics performance improvement system, including your evaluation, organizational learning, and innovation processes?
– Which customers cant participate in our Prescriptive Analytics domain because they lack skills, wealth, or convenient access to existing solutions?
– What are direct examples that show predictive analytics to be highly reliable?
Structured data Critical Criteria:
Jump start Structured data strategies and report on the economics of relationships managing Structured data and constraints.
– 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)?
– What knowledge, skills and characteristics mark a good Prescriptive Analytics project manager?
– Should you use a hierarchy or would a more structured database-model work best?
– How to deal with Prescriptive Analytics Changes?
Unstructured data Critical Criteria:
Adapt Unstructured data tactics and find the ideas you already have.
Utility companies Critical Criteria:
Scrutinze Utility companies visions and explore and align the progress in Utility companies.
– 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?
– Is Prescriptive Analytics Required?
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 | http://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.
To address the criteria in this checklist, these selected resources are provided for sources of further research and information:
Prescriptive Analytics External links:
Healthcare Prescriptive Analytics – Cedar Gate Technologies
Applied statistics External links:
Master of Applied Statistics (Online) | Statistics
Journal of Applied Statistics: Vol 45, No 5 – tandfonline.com
Big data External links:
Take 5 Media Group – Build an audience using big data
Business Intelligence and Big Data Analytics Software
Databricks – Making Big Data Simple
Business analytics External links:
Harvard Business Analytics Program
What is Business Analytics? Webopedia Definition
Business intelligence External links:
SQL Server Business Intelligence | Microsoft
EnsembleIQ | The premier business intelligence resource
Business operations External links:
U.S. Forest Service – Business Operations
Business Operations – ASAE
Business Operations Manager Jobs, Employment | …
Business process External links:
Microsoft Dynamics 365 – Modernizing Business Process …
HEFLO BPM | Business Process Management
Infosys BPM – Business Process Management | BPM Solutions
Computational model External links:
A Computational Model of Music Composition – DASH Harvard
[quant-ph/0108067] Computational model underlying the …
Computational science External links:
Welcome | School of Computational Science and Engineering
Computational Science and Engineering – NCAT
Computational Science and Engineering Education
Data mining External links:
Data mining | computer science | Britannica.com
UT Data Mining
What is Data Mining in Healthcare?
Decision Engineering External links:
Emergency Decision Engineering Model Based on …
decisionz.com – Decision Engineering (NZ) Ltd, Rated Web …
Decision Management External links:
Decision Management Solutions | Sapiens DECISION
Decision Management – SourceWatch
Health, Safety and Environment External links:
Health, Safety and Environment Policies – Manual
Health, Safety and Environment (HSE) Practices – Anadarko
Welcome to the Department of Health, Safety and Environment
Health care provider External links:
Health Care Provider Solutions – Optum
Map reduce External links:
Map Reduce | JavaShine
Joins with Map Reduce | Source Open
Map Reduce | JavaShine | Page 2
Mathematical model External links:
LCA Mathematical Model | The Methodology Center
Mathematical model – ScienceDaily
Mathematical sciences External links:
Mathematical Sciences – University of Delaware
Mathematical Sciences – Montclair State University
College of Natural and Mathematical Sciences – UMBC
Natural gas prices External links:
Natural Gas Prices & Rate Plans – Gas South
NGI Natural Gas Prices – Algonquin Citygate – Daily
U.S. Natural Gas Prices
Operations research External links:
Operations Research on JSTOR
Operations Research (O.R.), or operational research in the U.K, is a discipline that deals with the application of advanced analytical methods to help make better decisions.
Operations research (Book, 1974) [WorldCat.org]
Predictive analytics External links:
Strategic Location Management & Predictive Analytics | Tango
Predictive Analytics Software, Social Listening | NewBrand
Customer Analytics & Predictive Analytics Tools for Business
Structured data External links:
What is structured data? – Definition from WhatIs.com
Structured Data Testing Tool – Google
Structured Data for Dummies – Search Engine Journal
Unstructured data External links:
Scale-Out NAS for Unstructured Data | Dell EMC US
Utility companies External links:
Entergy Utility Companies – Scam Alert