Why buy when you can get it for free?
Back at you! Here is the fifth fantastic delivery of an amazing and fabulous selection of free and widely available business analytics learning content, which has been prepared just for you.
Corporate Social Responsibility (CSR) Analytics Sometimes seen as mere window dressing, CSR is ostensibly corporate self-regulation that seeks to ensure that a business not only actively complies with the letter of the law but also with the spirit of the law. CSR strategies encourage the company to make a positive impact on the environment and stakeholders including consumers, employees, investors, communities, and others. https://en.wikipedia.org/wiki/Corporate_social_responsibility
CSR Analytics can be used to measure and influence the management of a number of key business facets related to CSR, including how CSR can affect and influence an organisations performance with regards to:
- Its competitive situation and advantage
- Its ability to attract, acquire, retain and nurture workers, associates, customers, clients and users
- The morale, commitment and productivity of employees and associates
- The views of stakeholders, investors, owners, donors, sponsors and the financial community
- Its relationship with companies, governments, political parties, unions, pressure groups, peers and industry governing and advisory bodies, the media, suppliers, customers and the communities in which it operates
So, clearly, under the umbrella of CSR there is a lot of data that can be accumulated, integrated and analysed.
Consider this: CSR Analytics isnt just about mining data from operational systems. There is far more to it. A lot of the analysis needs to be built on a solid foundation of professional-grade qualitative research.
Environmental Impact Analytics This is a very important aspect of business, especially with the inevitable increase in legislation regarding combatting climate change and the minimisation of environmental damage casused by business. The analysis part of this is about assessing what impact your business has on the environment. It includes the complete chain of production, supply and service, from raw materials, through process and distribution, right through to eventual disposal and reuse of goods and materials.
The analysis of a businesss environmental impact is very much tied to the formal assessment of environmental impacts. Environmental assessment has been defined as the assessment of the environmental consequences (positive and negative) of a plan, policy, program, or project prior to the decision to move forward with the proposed action. In this context, the term environmental impact assessment (EIA) is usually used when applied to concrete projects and the term strategic environmental assessment applies to policies, plans and programmes (Fischer, 2016).
Environmental assessments may be governed by rules of administrative procedure regarding public participation and documentation of decision making, and may be subject to judicial review. https://en.wikipedia.org/wiki/Environmental_impact_assessment
Consider this: If you are interested in this subject I suggest you take a look at the wide range of instruments in the Environmental policy of the European Union. Among them the European Union has established a mix of mandatory and discretionary procedures to assess environmental impacts. https://en.wikipedia.org/wiki/Environmental_policy_of_the_European_Union
Project and Programme Analytics
Six Sigma and Lean analytics Six Sigma is a set of techniques and tools for process improvement. It was introduced by engineer Bill Smith while working at Motorola in 1986. Jack Welch made it central to his business strategy at General Electric in 1995. Today, it is used in many industrial sectors. https://en.wikipedia.org/wiki/Six_Sigma Conversely, Lean Six Sigma is a methodology that relies on a collaborative team effort to improve performance by systematically removing waste; combining lean manufacturing/lean enterprise and Six Sigma to eliminate the eight kinds of waste (muda): Time, Inventory, Motion, Waiting, Over production, Over processing, Defects, and Skills (abbreviated as TIMWOODS). https://en.wikipedia.org/wiki/Lean_Six_Sigma
Consider this: Visionary data science executive Vincent Granville in a piece entitled 16 analytic disciplines compared to data science, had this to say about Six Sigma: You could say that six sigma is a much more simple if not simplistic version of operations research (see above entry), where statistical modeling is kept to a minimum. Risks: non qualified people use non-robust black-box statistical tools to solve problems, it can result in disasters. In some ways, six sigma is a discipline more suited for business analysts (see business intelligence entry below) than for serious statisticians. https://www.datasciencecentral.com/profiles/blogs/17-analytic-disciplines-compared
Core competency analytics You are in business, and you want to keep tabs on:
- What intrinsically do you have in your organisation (specifically competencies) that would facilitate entry into a wide variety of markets?
- What facets of your organisation make significant contributions to the perceived customer benefits of the end products?
- What competencies do you have in your organisation that your competitors would find difficult to emulate?
This requires a mix of qualitative and quantitative analysis, and much of the data required will not be stored in systems, but in peoples heads.
Consider this: Make sure your team is competent in the practice of effective knowledge elicitation (tacit and implicit) as well as data integration and model building. You may also like take a look at a piece entitled The Core Competence of the Corporation, written by C. K. Prahalad and Gary Hamel, and published in the HBR in their May-June 1990 issue. https://hbr.org/1990/05/the-core-competence-of-the-corporation
Many thanks for reading.
You may be interested in other articles I have written:
Free Business Analytics Content Part 1
Free Business Analytics Content Part 2
Free Business Analytics Content Part 3
Free Business Analytics Content – Part 4
