The Adaptive Reference System (ARS) is a TOOL which is used to evaluate organization's performance. ARS can adapt easily to any organizational environment change by tracking three very specific values: Standard Value (ARS(Cr; SV )), Expected Value (ARS(Cr;ExV )) and Actual Value (ARS(Cr;AV )).
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The Adaptive Reference Systems initially started as a PhD research thesis proposed to be carried out in 4 steps: 1. Define ARS as a new concept in the literature; 2. Define Organizational Culture indicators according to ARS; 3. Use Cultural indicators to identify behavioral patterns in organizational management; 4. Integrate Culture Indicators in a Decision Support Systems for more efficient results in Project Management
Adaptive reference system: a tool for measuring managerial performance - article published in STUDIA UNIV. BABES–BOLYAI, INFORMATICA, Volume LX, Number 1, 2015
Read moreA computational perspective of the organizational culture evaluation - article published in STUDIA UNIV. BABES–BOLYAI, INFORMATICA, Volume LXI, Number 2, 2016
Read moreA New Perspective Over the Risk Assessment in Credit Scoring Analysis Using the Adaptive Reference System (ARS) - article published in 2016 in Springer Business Information Systems
Read moreNew Perspectives in Performance Management: Appraising Employees Based on Computer Usage Patterns - article published in 2019 in Springer Proceedings in Business and Economics
Read moreBeyond Rules of Engagement: An Adaptive Reference System for Ethical Decision-Making in Military AI - chapter in a Peter Lang published book
Read moreThis is an application of the Adaptive Reference System (ARS) to the domain of clinical gastroenterology. By mapping ESGE quality indicators we construct a Department Culture Indicator for a Gastroenterology / Endoscopy department.
Read moreA traditional decision making system evaluates the probability of a certain scenario to take place. That means it is an activity that is evaluated BEFORE making decisions. Like this, the system is empowered with a quasi-complete set of parameters that help the managers to take the best suitable decision based on that fixed context. But this only helps good/average companies to maintain their routinely course.
Making the leap from good/average to great (i.e. excellence in performance) needs more than that. To make such leap most of the time you need to "think out of the box". Thinking out of the box can be risky of course (which explains why risk-aversive Organizations have difficulties in implementing such measures), but yet extremely worthy if it turns out positively. In order to train a mind to "think outside the box" you need to evaluate performance, identify thinking patterns, improve the worthy patterns (or implement them if missing) and apply them on a bigger scale. That means you need to evaluate the activity AFTER making decisions and use it as a context for future decisions.
Use the framework to answer four distinct management questions: (1) Is there a systemic problem (all contributors below standard) or an individual outlier? (2) Is the department's culture trajectory improving, stable, or declining across sessions? (3) Which contributor is ready for promotion (AV consistently exceeds ExV at their level) and which needs a performance plan? (4) Did a specific intervention (new tool, training, process change) shift the culture indicator in the next session?
Identify 4–8 measurable performance criteria for each area of interest. For each criterion you need: a code/name, a Standard Value (SV - the external or industry benchmark), an Expected Value (ExV - your internal aspiration), and an Importance Weight on a 0–10 scale.
Assign higher weights to criteria that are most consequential for your domain (in the paper, ADR = 10 because it predicts cancer outcomes; your equivalent might be revenue conversion, SLA compliance, etc.).
Don't evaluate a junior contributor against a senior benchmark. Define 3–5 levels (e.g. Trainee / Junior / Senior / Expert) and calibrate the SV and ExV per level. The Standard Value may be lower for entry-level roles; the Expected Value climbs with seniority. This makes performance gaps meaningful rather than artifacts of experience differences.
Agree on a cadence - quarterly is recommended. Each Evaluation Session (ES₁, ES₂, …) captures the Actual Value (AV) for every criterion, per contributor, for that period. This is the raw data input to all subsequent calculations.
Construct a table where rows are Evaluation Sessions and columns are criteria (each split into SV / ExV / AV sub-columns). Populate AVs from your data source at the end of each session. The matrix is the longitudinal record from which all culture indicators are derived.
For each contributor in a session, compute their Actual Culture score as the weighted sum of their AVs across all criteria. Compute their Expected Culture target the same way using ExVs. The gap Δ = C − AC tells you whether they are above expectations (Δ < 0), on target (Δ ≈ 0), or underperforming (Δ > 0).
Average the individual AV scores across all contributors in the team/unit, then apply the same weighted sum formula, multiplied by the Area of Interest Importance Weight. Compute the expected counterpart with ExVs. Track both numbers across sessions to reveal trajectory.
Aggregate the Area of Interest scores across all AoIs within the department, weighted by each AoI's importance weight, then multiply by the Department Importance Weight. The department-level gap tells management whether the whole unit is moving toward or away from its expected performance culture.
Sum the department culture indicators across all departments, each already scaled by its own. This single number is what goes to governing boards.
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Any business starts with an idea and a vision. The idea is usually the description of what to do and the vision is the description of how to do it. A successful business is hardly given by the idea as it is mostly by its implementation, generically given by the vision. This current paper is aiming to give a possible answer of how to track and improve both the idea and the vision using computed versions of economical notions such as Company Culture, Department Culture, Technology Culture, etc. which all together can combine to provide a valuable feedback to measure the deviations from the initial vision and idea.
Transilvae Trading SRL, Cluj-Napoca, Romania, 407280