Lecture 6: Organisational evidence Flashcards
(13 cards)
what is Organizational evidence?
- Recorded as part of operational activities
- by the government organisation are requeires to express historyically to account what they do
- Helps make decisions
- Helps monitor performance
- May be necessary for legal compliance
- “Represents one of the richest sources of evidence for managers” (p175)
- Helps identify problems or challenges
- Recognizes potential cause(s) of a problem
- It may also recognize opportunities
- one of the riches sources for managers as we turn to ourselves
- causes issues for cognitive bias
Data, information, and evidence
- These terms are often used interchangeably – but they differ (pp176-177)
- Data: numbers, words, figures, symbols, sounds, dates, images etc without context
- Information: data relating to something or someone and considered meaningful or useful
- Evidence: information supporting (or contradicting) a claim, assumption or hypothesis
What counts as organizational evidence?
Qualitative data
- Statements about the organizations ‘strategic purpose’ (Mission, Objectives, others)
- Estimations (e.g profit warning to the Stock Exchange)
- The increasing use of ‘narrative’ and ‘storytelling’ in organizational accounts of events
- Primary and secondary data
Quantitative data
- Audited financial accounts
- Bank account statements
- Budgetary processes
- Financial forecasts
- Physical or digital records – with dates
- Customer interaction levels
- Customer behaviour data
- Primary and secondary data
- both matter
- limitations of both
- both have merits
Who looks for evidence from the organization?
- Government auditors (Audit Scotland)
- Accreditation bodies
- Business media (on performance and sales)
- Regulatory bodies (UEFA’s Financial Sustainability Rules)
- Inquiry bodies (Fatal Accident Inquiry)
- Awards bodies
- Banks and investors (loans and investing)
- Court and justice systems
- Customers, patients etc.
- Planners (forecasting)
What questions to ask? pp177-179
- What is the problem?
- Does organizational evidence confirm the problem?
- Is there a trend?
- What organizational consequences of the problem does the evidence indicate?
- Does the evidence confirm the assumed causal mechanism?
- What is the preferred solution?
- Is there an association between the preferred solution and the favoured organizational outcomes?
what to ask?
What is the problem4 (what, who, when, where)?
Does organizational evidence confirm the problem?
Is there a trend (does the evidence suggest that the problem will worsen if nothing is done)?
What organizational consequences of the problem does the evidence indicate?
Does the evidence confirm the assumed causal mechanism? (Is there a correlation between the assumed cause, the problem and its organizational consequences?)
What is the preferred solution (what, who, when, where)?
Does organizational evidence confirm the assumed causal mechanism: is there an association between the preferred solution and the favoured organizational outcomes?
We note that organizational data may also be gathered in anticipation of future needs, as opposed to current problems.
What types of organizational evidence are typically available?
Finance and accounting
statements of cash flow – a record of money received or given out;
income statements – lists of an organization’s profit or loss and income;
statements of a firm’s financial position (also known as a balance sheet) – lists of an organization’s assets (money or things they own) and liabilities (money or things they owe).
Human resources
Human resource evidence is fundamentally about people: who they are, their characteristics and their relationship to the organization.
Sales and marketing
Sales and marketing evidence includes facts about the number of products or services sold, market share, competitors, details of customer relationships, brand awareness and the impact of marketing campaigns.
Risk
Large companies typically have departments that manage and assess the multiple risks that can impact the organization
Production
evidence relates to the products or services that an organization creates, including measures of inputs, outputs and the overall quality level.
Quality and performance
Larger organizations often capture data to monitor, control and ensure the quality of their products or services.
Customer service
Specific customer service functions deal with client interactions that do not involve selling or production.
Where to find organizational evidence
Databases and information systems
Databases usually are the core systems for capturing and processing many of the organization’s daily activities.
Document and content management systems
A great many organizational data are stored in the form of documents or spreadsheets rather than as structured data in a database or data warehouse.
Workflow systems
These are systems that manage the execution of a business process. Workflow systems are often hybrids between data and document-based systems: generating and storing both data and whole documents.
Physical records
Many organizations still use physical records, including documents in filing cabinets. This could be because of lack of funds to invest in new technology, legal requirements or simply habit.
Staff
A great deal of organizational evidence exists at staff level. For example, relevant data may be kept by individual staff members on their own PCs, on shared drives or in the form of physical records
Industry bodies, professional associations and census bureaux
Industry bodies, professional associations and census bureaux often have relevant, high-quality information about an organization, its competitors and industry or sector.
Social media
Relatively novel, but increasingly important, sources of organizational evidence are social media sites such as Facebook and Twitter. Not only do social media generate data regarding customer satisfaction, brand awareness, brand identity or perceived quality, but they also provide information about the organization’s relationship with society.
External stakeholders
External stakeholders such as customers, regulators, shareholders, suppliers and even the society at large may be an important source of evidence about a specific organization. These external stakeholders are a rich source of opinions about the output, results, interactions and behaviour of an organization.
Techniques and tools for acquiring data
Management information and business intelligence systems
There are many specialized tools available to extract data from both core processing systems and specifically designed reporting systems. The purpose of these systems is to support the decision-making process by organizing, processing and analysing the data and turning them into useful information.
Querying existing databases and systems using Structured Query Language
Most information systems store data in an underlying database (ie data warehouse).
Analysing organizational data using statistical software
Choosing statistical software and/or a data analytics tool is a trade-off between costs, benefits and ease of usage. The downside is it is costly
Review of documents and reports
A review of documents can be a quick and easy method of uncovering useful organizational data. It can be done with or without the assistance of specialist software such as a program for content analysis or text mining.
Surveys
A common form of acquiring organizational data is the survey. As explained in Chapter 3, effective survey design requires training to avoid bias.
Organizational data turned into information
Besides categorizing organizational evidence based on the function or physical location of its original data, organizational evidence can be thought about in terms of the value it adds to the organization’s decision-making.
Organizations produce operational data during everyday tasks (e.g. sales, production, customer service). These data are mostly descriptive and often retrospective, showing what has happened. Though useful, individual pieces (like a single sale) usually have limited value until aggregated into broader organizational information (e.g. monthly sales reports, HR statistics), which help managers identify trends and assess overall performance.
Metrics are numerical measures that help track performance. When these metrics are linked to specific goals or targets critical to organizational success, they become Key Performance Indicators (KPIs). KPIs provide context by indicating how performance compares to expectations. They can track progress, highlight issues, and guide decisions, often through visual formats like traffic-light (RAG) systems. However, not all KPIs are based on hard data—some may rely on subjective judgment.
Benchmarks are metrics compared against external standards or best practices. Benchmarking involves using these comparisons to improve performance by identifying gaps and learning from top-performing organizations. Still, one must evaluate whether the benchmark is truly valid and appropriate for their own context—what works well in one setting may not be suitable elsewhere.
Correlations and regressions are inferential tools. A correlation shows when two metrics move together (e.g. hot weather and ice cream sales). A regression allows prediction—how much change in one variable (like temperature) predicts change in another (like sales). These techniques help uncover cause-effect links and make forecasts but must be used carefully to avoid misleading conclusions.
Predictive models are statistical or algorithmic systems (including those using AI or machine learning) that forecast outcomes based on patterns in data. They can identify key drivers of success or risk, supporting evidence-based decision-making. Despite their advanced capabilities, predictive models must still be used critically—validity depends heavily on the quality and relevance of the underlying data.
Other considerations when acquiring data
Data protection/information security
There are many laws and regulations aimed at keeping employees’ sensitive information safe and the privacy of customers secure. These include the Data Protection Act (1998) in the United Kingdom, the General Data Protection Regulation (2016) in the European Union, and the Federal Information Security Management Act (2002) in the United States. We need to consider the impact of these laws when using organizational data. Multinational firms in particular may be impacted by different, sometimes conflicting.
Costs and benefits
Acquiring and analysing organizational data may come at a considerable price, so a thorough assessment of the expected costs and benefits is important. Several large companies have invested millions of dollars in building data warehouses or implementing big data projects where the quality of the data fed into the systems was so weak the cost expended was unwarranted.
Accessibility
While some organizational data may be captured and stored in an easily accessible central database, much is likely to be dispersed across the organization, especially in large and complex companies. Acquiring data from multiple systems and locations may require a lot of time and effort. In addition, when we lack a common identifier, it will be very hard to link together data from different systems. For this reason, we often require assistance from an internal IT department or an external data analytics expert.
Politics
Finally, internal politics sometimes stand in the way of successful use of organizational evidence. Even when we capture and store data in an accessible database and have sufficient knowledge of data analytics we still may face challenges in using organizational evidence to support decision-making. In fact, lack of executive sponsorship is consistently cited as the main reason data analytics projects fail. One of the reasons is that evidence-based management sometimes challenges authority. It brings in evidence that may contradict the intuition and judgement of business leaders.
