♜Strategic Management: Risk Analysis (Definitions)

 "The evaluation, classification, and prioritization of risks." (Sandy Shrum et al, "CMMI®: Guidelines for Process Integration and Product Improvement", 2003)

"The process of identifying, characterizing, and prioritizing risks." (Richard D Stutzke, "Estimating Software-Intensive Systems: Projects, Products, and Processes", 2005)

"The process of assessing identified risks to estimate their impact and probability of occurrence (likelihood)." (Tilo Linz et al, "Software Testing Practice: Test Management", 2007)

"The process of measuring and analyzing the risks associated with financial and investment decisions. Risk refers to the variability of expected returns (earnings or cash flows)." (Jae K Shim & Joel G Siegel, "Budgeting Basics and Beyond", 2008)

"A formal definition of risks based on asset identification, threat enumeration, and consequence evaluation." (Mark Rhodes-Ousley, "Information Security: The Complete Reference" 2nd Ed., 2013)

"Systematic use of available information to determine how often specified events may occur and the magnitude of their likely consequences." (Chartered Institute of Building, "Code of Practice for Project Management for Construction and Development" 5th Ed., 2014)

"The process to comprehend the nature of risk and to determine the level of risk [3]" (David Sutton, "Information Risk Management: A practitioner’s guide", 2014)

"This is the part where we combine the impact and the likelihood (or probability) to calculate the level of risk and to plot it onto a risk matrix, which allows us to compare risks for their severity and to decide which are in greatest need of treatment." (David Sutton, "Information Risk Management: A practitioner’s guide", 2014)

"Determining the nature and likelihood of the risks to key data" (Nell Dale & John Lewis, "Computer Science Illuminated" 6th Ed., 2015)

"A process undertaken to comprehend the nature of risk and to determine the level of risk." (William Stallings, "Effective Cybersecurity: A Guide to Using Best Practices and Standards", 2018)

"The process of assessing identified risks to estimate their impact and probability of occurrence (likelihood)." (IQBBA)

"The process to comprehend the nature of risk and to determine the level of risk" (ISO Guide 73:2009)

♜Strategic Management: Risk Matrix (Definitions)

"A graph that compares the likelihood and severity of risks from highest to lowest." (Annetta Cortez & Bob Yehling, "The Complete Idiot's Guide® To Risk Management", 2010)

"A common way to determine whether a risk is considered low, moderate, or high by combining the two dimensions of a risk: its probability of occurrence and its impact on objectives if it occurs." (Cynthia Stackpole, "PMP Certification All-in-One For Dummies", 2011)

"A grid for mapping the probability of each risk occurrence and its impact on project objectives if that risk occurs. " (Project Management Institute, "The Standard for Portfolio Management" 3rd Ed., 2012)

"A graphical representation of impact versus likelihood used to assist in the prioritisation of risks" (David Sutton, "Information Risk Management: A practitioner’s guide", 2014)

[impact matrix:] "A method for assigning values to expected pressures from the macro-environment in order for an organisation to assess the future nature of its context for which it must design an effective strategy." (Duncan Angwin & Stephen Cummings, "The Strategy Pathfinder" 3rd Ed., 2017)

🧭Business Intelligence: Perspectives (Part 3: Self-Service BI)

Introduction

According to Gartner, the world's leading information technology research and advisory company, Self-Service BI (aka self-service analytics, ad-hoc analysis, personal analytics), for short SSBI, is a “form of business intelligence (BI) in which line-of-business professionals are enabled and encouraged to perform queries and generate reports on their own, with nominal IT support” [1].

Reading between the lines, SSBI presumes the existence of an infrastructure made of tools to support it (aka self-service BI tools), direct or indirect access to row data and/or data models for the users, and the skillset needed in order to work with data and answer to business problems/questions.

A Little History

The concept of self-service is not new, it just got “rebranded” and transformed into a business opportunity. The need for business users to perform ad-hoc analyses was always there in organizations, especially in the ones not having the right infrastructure for harnessing their data. Even since the 90s with the appearance of products like MS Excel or MS Access in many organizations users were forced by the state of art to learn how to use such products in order to get the answers they needed from the data. Users started building personal solutions, many of them temporary, intended to fill the reporting gaps organizations had. With a little effort and relatively small investment users had the possibility of playing with the data, understanding the data, identifying and solving problems in the business. They acquired thus a certain level of business expertise and data awareness becoming valuable resources in the organization.

With time such solutions grew in scope and data volume, gained broader visibility and reached deeper in organizations, some of them becoming team, departmental or cross-departmental solutions. What grows uncontrolled with time starts to have negative impact on the environment. First tools’ management became a problem because the solutions needed to be backed-up and maintained regularly, then other problems started to surface: security of data, inefficient data processing as increasing volumes of data were processed on local computers and transferred over the network, data and effort were duplicated, different versions of reality existed as different numbers were reported, numbers that were reflecting different definitions, knowledge about the business or data-analysis skillsets. The management needed a more consolidated and standardized effort in order to address these problems. Organizations were forced or embraced the idea of investing money in modern BI solutions, in more powerful servers capable of handling a larger amount of requests, in flexible data models that facilitate data consumption, in data quality initiatives. Thus through various projects a considerable number of such solutions were converted into more standardized and performant BI solutions, the IT department being in control of the changes and new requests.

Back to Present

With IT in control of the reporting requirements the business is forced to rely on the rapidity with which IT is able to address new requirements. Some organizations acquired internal resources in order to build reports and afferent infrastructure in-house, others created partnerships with vendors, or approached a combination of the two. As the volume of requirements isn’t uniform over time, the business has to wait several days between the time a requirement was addressed to IT and a solution was provided. In business terms a few of days of waiting for data can equate with the loss of an opportunity, a decision taken too late, decision that could have broader impact.

A few years ago things started to change when the ad-hoc analysis concept was rebranded as self-service and surfaced as trend. This time vendors like Qlik, Tableau, MicroStrategy or Microsoft, some of the main SSBI vendors, are offering easy to use and rich functionality tools for data integration, visualization and discovery, tools that reflect the advances made in graphics, data storage and processing technologies (e.g. in-memory databases, parallel processing). With just a few drag-and-drops users are able to display details, aggregate data, identify trends and correlations between data. In addition the tools can make use of the existing data models available in data warehouses, data marts and other types of data repositories, including the rich set of open data available on the web.

Looking at the Future

Like its predecessors, SSBI seems to address primarily data analysts and data-aware business users (aka data citizens), however in time is expected to be adopted by more organizations and become more mature where already adopted. Of course, some of the problems from the early days more likely will resurface though through governance, better architectures and tools, integration with other BI capabilities, trainings and awareness most of the problems will be overcome. More likely there will be also organizations in which SSBI will fail. In the end each organization will need to find by itself the value of SSBI.

Previous Post <<||>> Next Post

Resources:
[1] Gartner (2016) Self-Service Analytics [Online] Available from: http://www.gartner.com/it-glossary/self-service-analytics
[2] Gartner (2016) Magic Quadrant for Business Intelligence and Analytics Platforms, by Josh Parenteau, Rita L. Sallam, Cindi Howson, Joao Tapadinhas, Kurt Schlegel, Thomas W. Oestreich [Online] Available from: https://www.gartner.com/doc/reprints?id=1-2XXET8P&ct=160204&st=sb

🧭Business Intelligence: Perspectives (Part 2: The Complexity Myth)

Introduction

While looking over “Business Intelligence Concepts and Platform Capabilities” Coursera MOOC resources for Module 2 I run into two similar articles from Solutions Review, respectively Information Age. What caught my attention was the easiness with which the complexity of BI “myth” is approached in both columns.

According to the two sources the capabilities of nowadays BI tools “enabled business users to easily identify and present trends in an impactful way” [1], and “do not require an expert at the helm” [2]. It became thus simpler for users to independently query data and create interactive reports and presentations [2]. In both columns one can read between the lines that the simplicity of using BI tools is equivalent with negating the complexity of BI, which from my point of view is false. In fact here are regarded especially the self-service BI tools, in trend nowadays, that allow users to easily perform ad-hoc analysis with a minimal involvement from IT. Self-service BI is only a subset of what BI for organizations means, and just a capability from the many BI capabilities an organization needs in theory, even if some organizations might use it extensively.

Beyond the Surface

A BI tool is not a BI solution per se, even if many generic BI solutions for different systems are available out of the box. This is one of the biggest confusion managers, users and unfortunately also BI professionals make. A BI tool offers the technological basis for creating a BI infrastructure, though it comes with no guarantees. It takes a well-defined IT and business strategy, one or more successful projects, skillful developers and users in order to harness the BI investment.

On the other side it’s also true that organizations can obtain results also from less, though BI doesn’t equates with any ad-hoc analysis performed by users, even if they use BI tools for this purpose. BI is not only about tools, reporting and revealing trends in the data. BI often implies a holistic knowledge about the business and certain data awareness, without which users will start aggregating and comparing apples with pears and wonder why they taste and look different.

If everything were so simple then why so many BI projects fail to deliver what’s expected? Why so many managers complain that they don’t have the data they need, when they need them? Sure maybe the problem lies in over-complexifying the whole BI landscape and treating everything from a high-level, though that’s more likely not it.

It’s a Teamwork Knowledge Game

BI is or needs to be monitoring and problem solving oriented. This requires a deep understanding about processes and business. There are business users and also BI professionals who don’t have the knowledge one needs in order to approach a business problem. One can see that from the premises they have, the questions they raise, the data they consider, the models they build, and the results.

From a BI professional’s perspective, even if one has a broad knowledge about various businesses, one often lacks the insight in a given business. BI professionals can seldom provide adequate BI solutions without input and feedback from the business. Some BI professionals rely too much on their knowledge, same as the business sometimes expects a maximum output from BI professionals by providing a minimum of input.

Considering the business users, quite often their focus and knowledge cover only the data boundaries of their department, while many problems extend over those boundaries. They know facts that are not necessarily reflected in the data. Even if they are closer to the data than other parties, they still lack some data-awareness (including statistical awareness) in order to approach problems.

Somebody was saying ironically when talking about users’ data and problem solving skills - “not everybody is a Bill Gates or Steve Jobs”. Continuing the idea, one can’t expect users to act as such. For sure there are many business users who are better problem solvers than BI consultants, though on the other side one can’t expect that the average business user will have the same skillset as an experienced BI consultant. This is in fact one of the problems of self-service BI. Probably with time and effort organization will develop such resources, though some help from BI professionals will be still needed. Without a good cooperation between the business and BI professionals an organization might not have the hoped results when investing in BI

More on Complexity

The complexity arises when one tries to make more with the data, especially the data found in raw form. Usually the complexity of raw data can be addressed by building a logical or physical model that allows easier consumption of data. Here is the point where the users find themselves overwhelmed, because for this is required a good knowledge of the physical data model and its semantics, the technical knowledge to build models and the skills to reengineer the logic available in the source systems. These are the themes BI professionals are supposed to excel in. Talking about models, they are the most difficult to build because they reflect various segments of the business, they reflect a breakdown of the complexity. It’s also the point where many BI projects fail as the built models don’t reflect the reality or aren’t capable to answer to business questions.

Coming back to the two columns, I have to point out that the complexity of a subject or domain can’t be judged based on how easy is to approach basic tasks. The complexity lies typically when one goes beyond the basics, when one dives into details. In case of BI its complexity starts when one attempts mixing various technologies and knowledge domains to model and solve daily business problems in an integrated, holistic, aligned, consistent and cost-effective manner. The more the technologies, the knowledge domains and constraints one has to consider, the more complex the BI landscape and solutions become.

On the other side this doesn’t mean that the BI infrastructure can’t be simplified, that BI can’t rely heavily or exclusively on self-service BI solutions. However for each strategy there are advantages and disadvantages and one more likely has to consider both sides of the coin in the process. And self-service BI has its own trade-offs, weaknesses that can be transformed in strengths with time.

Conclusion

When one considers nowadays BI tools capabilities, ad-hoc analyses are relatively easy to perform and can lead to results, though such analyses don’t equate with BI and the simplicity with which they are performed don’t necessarily imply that BI is simple as a whole. When one considers the complexity of nowadays businesses, the more one dives in various problems a business has, the more complex the BI landscape seems. In the end it’s in each organization powers to simplify and harmonize its BI infrastructure to a degree that its business goals aren’t affected negatively.

Previous Post <<||>> Next Post

Resources
[1] Information Age (2015) 5 Myths about Intelligence, by Ben Rossi, [Online] Available from: http://www.information-age.com/technology/information-management/123460271/5-myths-about-business-intelligence 
[2] SolutionsReview (2015) Top 5 Business Intelligence Myths Revealed, by Timothy King, [Online] Available from: http://solutionsreview.com/business-intelligence/top-5-business-intelligence-myths-revealed
[3] Gartner (2016) Magic Quadrant for Business Intelligence and Analytics Platforms, by Josh Parenteau, Rita L. Sallam, Cindi Howson, Joao Tapadinhas, Kurt Schlegel, Thomas W. Oestreich [Online] Available from: https://www.gartner.com/doc/reprints?id=1-2XXET8P&ct=160204&st=sb 
[4] Coursera (2016) Business Intelligence Concepts, Tools, and Applications MOOC, led by Jahangir Karimi, University of Colorado, [Online] Available from: https://www.coursera.org/learn/business-intelligence-tools

♜Strategic Management: Benefit (Definitions)

"Something of value as perceived by a customer." (Steven Haines, "The Product Manager's Desk Reference", 2008)

"As it pertains to products and services, what problem a product or service solves or what need it fulfills for customers." (Gina Abudi & Brandon Toropov, "The Complete Idiot's Guide to Best Practices for Small Business", 2011)

"The improvement resulting from outcomes perceived and expressed in terms of advantages for the organization, such as decreases in operating costs or product failures and increases in profit or productivity." (Paul C Dinsmore et al, "Enterprise Project Governance", 2012)

"An outcome of actions, behaviors, products, or services that provide utility to the sponsoring organization as well as to the program's intended beneficiaries." (Project Management Institute, "The Standard for Program Management" 3rd Ed., 2013)

"A description of a product advantage written from the perspective of the customer. Often includes emotional aspects." (Pamela Schure & Brian Lawley, "Product Management For Dummies", 2017)

♜Strategic Management: SWOT Analysis (Definitions)

"A scan of the business environment to identify the organization's strengths and weaknesses and the opportunities and threats it faces." (Teri Lund & Susan Barksdale, "10 Steps to Successful Strategic Planning", 2006)

"A general method used as an element of strategic planning. SWOT is an acronym for strengths, weaknesses, opportunities, and threats. Within the context of Product Management, SWOT is used to synthesize the many elements of the business environment for a product or product line (as opposed to a corporate or divisional entity). The generalized quadrant structure of the SWOT model is used." (Steven Haines, "The Product Manager's Desk Reference", 2008)

"A method of analyzing a situation or business to determine whether it’s viable." (Sue Johnson & Gwen Moran, "The Complete Idiot's Guide To Business Plans", 2010)

"A method that enables companies to view strengths, weaknesses, opportunities, and threats together." (Annetta Cortez & Bob Yehling, "The Complete Idiot's Guide® To Risk Management", 2010)

"A planning method used to evaluate the strengths, weaknesses, opportunities, and threats involved in a particular strategic direction for your business." (Gina Abudi & Brandon Toropov, "The Complete Idiot's Guide to Best Practices for Small Business", 2011)

 "A type of analysis that provides companies with both internal and external factors that could affect the long-term success of the company." (DAMA International, "The DAMA Dictionary of Data Management", 2011)

"An analysis used to determine strength and weak sides of the performance of an organization and to identify opportunities and dangers in the form of weaknesses and both internal and external threats. The four attributes of SWOT are: Strengths, Weaknesses, Opportunities, Threats." (International Qualifications Board for Business Analysis, "Standard glossary of terms used in Software Engineering", 2011)

"Involves the evaluation of strengths and weaknesses, which are internal factors, and opportunities and threats, which are external factors." (Linda Volonino & Efraim Turban, "Information Technology for Management" 8th Ed., 2011)

"Method of studying and identifying an organization's strengths, weaknesses, opportunities, and threats." (Leslie G Eldenburg & Susan K Wolcott, "Cost Management" 2nd Ed., 2011)

"This information gathering technique examines the project from the perspective of each project's strengths, weaknesses, opportunities, and threats to increase the breadth of the risks considered by risk management." (Cynthia Stackpole, "PMP Certification All-in-One For Dummies", 2011)

"A problem-solving or decision analysis technique in which strengths, weaknesses, opportunities, and threats to the project or organization are examined." (Bonnie Biafore & Teresa Stover, "Your Project Management Coach: Best Practices for Managing Projects in the Real World", 2012)

"A SWOT analysis is an approach to developing strategy that begins by identifying an organization’s strengths, weaknesses, opportunities, and threats (hence SWOT). From these categories, an organization can identify ways to build on its strengths, improve its weaknesses, take advantage of opportunities, and minimize the potential impact of threats." (Laura Sebastian-Coleman, "Measuring Data Quality for Ongoing Improvement ", 2012)

"An analysis process highlighting strengths, weaknesses, opportunities, and threats to an entity." (Joan C Dessinger, "Fundamentals of Performance Improvement" 3rd Ed., 2012)

"The analysis of strengths, weaknesses, opportunities, and threats of an organization, project, or option." (Project Management Institute, "Navigating Complexity: A Practice Guide", 2014)

"An analysis of the company’s strengths and weaknesses compared to the opportunities and threats in the market place." (Pamela Schure & Brian Lawley, "Product Management For Dummies", 2017)

"Analysis of strengths, weaknesses, opportunities, and threats of an organization, project, or option." (Project Management Institute, "A Guide to the Project Management Body of Knowledge (PMBOK Guide)", 2017)

"The main purpose of this analysis is to determine the extent to which an organisation 'fits' with the demands of its context." (Duncan Angwin & Stephen Cummings, "The Strategy Pathfinder 3rd Ed.", 2017)

"The SWOT framework classifies the factors relevant for a firm’s strategic decision making into four categories: strengths, weaknesses, opportunities, and threats." (Robert M Grant, "Contemporary Strategy Analysis" 10th Ed., 2018)

"Technique that reviews and analyses the internal strength and weakness of an organization, and the external opportunities and threats it faces" (ITIL)

♜Strategic Management: Management System (Definitions)

[strategic management system:] "A comprehensive system to lead, manage, and change our total organization in a conscious, well planned out, and integrated fashion, based on our core strategies (and using research that works) to develop and achieve our ideal future vision."

"A Business Management System is a set of tools for planning and implementing policies, practices, guidelines, processes and procedures that are used in the development, deployment and execution of business plans and strategies and all associated management activities."  (Black's Law Dictionary 2nd Ed.)

"Management Systems are systematic frameworks designed to manage an organization's policies, procedures and processes and promote continual improvement within." (BSI) [source]

"System to establish policy and objectives to achieve those objectives" (ISO 9000)