AI-Powered Dynamic OKR KPI and KAs Key Actions Automated Production and Display Model

Abstract

The invention relates to a model that enables the automated and dynamic analysis of raw data flowing into an organization by artificial intelligence, transforming it into goals (OKRs), performance indicators (KPIs), and key actions (KAs) required to achieve those goals, and then visualizing this data, within the fields of corporate performance management, business intelligence (BI), strategic planning, and data analytics.

Description

1 TARIFF AI-Powered Dynamic OKR KPIs and KAs Key Actions Automated Production and Presentation Model Technical Area The invention relates to corporate performance management, business intelligence (BI), and strategic planning. In the fields of planning and data analytics; raw data flowing into the organization is processed by artificial intelligence. analyzed automatically and dynamically to achieve targets (OKR), performance indicators (KPIs) and the key actions (KAs) required to achieve these goals. 10 It relates to a model used for the purpose of transformation and visualization. State of the Art Nowadays, corporate goals (OKRs) and metrics (KPIs) are usually determined manually at the beginning of the year. This is determined and reflected in static business intelligence dashboards (PowerBI, Tableau, etc.). The current 15 In this situation, there is a "semantic disconnect" between raw data and strategic objectives. Market When conditions or network / system performance change instantaneously, the predetermined Static KPIs can become meaningless. Furthermore, when a KPI target is not met... Current systems only provide a "red alert"; what "Actions" can be taken to correct this situation? It cannot produce and present to decision-makers the idea that "(KAs)" should be taken. The mentioned and existing 20 Problems that could not be solved with current technical methods necessitated an innovation in the relevant technical field. Purpose of the Invention The present invention aims to eliminate the aforementioned disadvantages and introduce new technologies to the relevant technical field. Dynamic OKR, KPI and KAs (Key Actions) automated production to bring advantages and 25 It is related to the representation model. The main goal of the invention is Generative Artificial Intelligence (GAI) and Causal Machine Learning. Using Causal ML (Causal ML) algorithms to view real-time data flow within the organization's data lake. The examiner not only reports on the current situation based on the data obtained, but also provides sub-assessments. Setting new dynamic KPIs for departments and stating "To reach a 90% score, use system X with 30..." Generating clear Key Actions (KAAs) such as "Update parameter Y" and organizing them hierarchically. The goal is to create a model that visualizes the tree structure. Another aim of the invention is to mathematically determine which change in which data affects which KPI. Causal Inference Networks, which enable mapping in this way, numerical deviations, clear, textual OKR and KA (Key Action) 35 that humans can understand Large Language Models (LLM) and KPI targets that convert anomaly detection into tangible elements 2 Dynamic, which enables automatic adaptation to market / system realities through its methods. It is about combining thresholding (dynamic thresholding) features. Another purpose of the invention is to analyze the millions of lines of technical and commercial data in the company's data lake. by constantly listening and using this data to primarily answer the question "Where are we right now?" It updates KPIs in real time, and if there is a deviation from the target in a KPI, this deviation is reflected in the company's 5 metrics generated by KPIs that calculate their impact on quarterly objectives By reviewing and learning from past data, the Data Science team decided, "To recover this KPI, we need to do the following..." Specific Key Actions such as "train the model," "network team should change this parameter" (Key Actions) are created and this entire causal chain is presented to the user interactively via a smart interface. The structural and characteristic features and all the advantages of the invention are given in the figures below and these 10 Thanks to the detailed explanation written with references to the figures, it becomes clearer. This will be understood, and therefore the evaluation should also take these figures and detailed explanations into account. It must be done by taking it. Figures to Help Understand the Invention 15 Figure 1 shows the general architecture of the system that is the subject of the invention. Explanation of Part References 1. Raw data integration layer 2. Database of defining values ​​20 3. Historical action database 4. AI strategy server 5. Dynamic targeting module 6. Data-KPI matching unit 7. OKR revision engine 25 8. Key Action (KAs) generator 9. Smart dashboard interface Detailed Description of the Invention In this detailed explanation, the preferred configurations of the invention are only 30% better understood in the subject. This is intended to facilitate understanding and will not impose any limiting effects. The invention is corporate. performance management, business intelligence (BI), strategic planning, and data analytics in these areas; raw data flowing into the institution is analyzed automatically by artificial intelligence and dynamically target objectives (OKRs), performance indicators (KPIs), and these objectives 35 It is a model that provides, and its feature is; second-by-second flow from different units such as network, sales, HR. 3 raw data integration layer (1) where numerical data is collected, created by the relevant KPIs The database of key values ​​in which metrics are kept (2), which action was taken in the past Historical action database (3) that keeps track of which KPI it affected and in what direction, making sense of the data AI strategy server (4), which is the central intelligence that dynamically calculates the target trees, Dynamic targeting module (5), the main algorithm that converts data into action, receives raw data. Data-KPI is an algorithm that calculates which existing KPIs are directly affected by the data. Matching unit (6), objectives (Objectives) and key results (Key Results) according to changing KPIs The OKR revision engine (7) updates the Results) to improve lagging metrics. Key Action (KAs) generator (8) that generates solution steps (tasks) with Generative AI, the user Smart dashboard 10 that displays the "Data -> KPI -> OKR -> Action to be Taken" chain on its screen. It includes the interface (9). The working principle of the invention model is as follows: The invention model works in the company's data lake (1) It constantly listens to millions of lines of technical and commercial data. The AI ​​strategy server (4) processes this data. Using the KPIs (6) which are the answer to the question "Where are we now?", in real time. updates. If there is a deviation from the target in a KPI, the OKR revision engine (7) updates this deviation by 15 It calculates the impact of traditional systems on the company's quarterly objectives. When it gets stuck, the KAs generator (8) comes into play and examines the metrics (2) created by the KPIs. and learns from past data (3), "To recover this KPI, the Data Science team uses the following model Specific Key Actions (Key Actions) such as "train them, the Network team should change this parameter" (Actions) creates. All this causal chain provides the user with an interactive smart dashboard (9) 20 It is presented through. The invention model performs the following functions: • Data from different sources (1, 2, 3) flows to the AI ​​server (4) and cleaning, • Detection of trends and instantaneous deviations in the data and scoring of existing KPIs (6), 25 • Low-scoring or excessively high-scoring KPIs affect the organization's overall OKRs (7) simulating the effect, • Optimal system for correcting target deviations or seizing opportunities Calculation of actions (8), • Textualization of calculated actions in "Key Actions (KAs)" format, 30 • Updated KPI, OKR and KAs data are available in the interactive panels of the relevant teams (9) visualization.

Claims

4 REQUESTS 1. Corporate performance management, business intelligence (BI), strategic In the fields of planning and data analytics; artificial intelligence of raw data flowing into the organization. By being analyzed, it automatically and dynamically targets (OKR), performance indicators (KPIs) and the 5 key factors needed to achieve these goals a model that enables the conversion and visualization of actions (KAs) Its characteristic is; • Digital data flowing in seconds from different units such as network, sales, HR, etc. raw data integration layer (1) where collected • 10 key values ​​where the metrics generated by the relevant KPIs are recorded database (2), • Tracks how past actions affected which KPIs and in what way. historical action database (3), • interprets data and dynamically calculates target trees AI strategy server, which is the central intelligence (4), 15 • Dynamic targeting module (5), which is the main algorithm that translates data into action, • Calculates which existing KPIs are directly affected by the incoming raw data. Data-KPI matching unit (6), which is an algorithm • Objectives and key results based on changing KPIs OKR revision engine (7), updated by Results), 20 • Solution steps with Generative AI to improve lagging metrics (tasks) generating Key Action (KAs) generator (8), • The "Data -> KPI -> OKR -> Action to be Taken" chain on the user's screen Smart dashboard interface showing (9) It includes. 25

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