Came across the article that captured my attention since. Check out “Strategic Alignment With AI and Smart KPIs” [1] by David Kiron, Michael Schrage, François Candelon, Shervin Khodabandeh, and Michael Chu. The key message is about the dynamic alignment of various key performance indicators (KPIs) on different organizational levels, which can hardly be done without the incorporation of AI technologies.
The traditional approach is to define KPIs once and stick to them often without taking into consideration the dynamic nature of the business environment and internal organizational changes. It was acceptable decades ago when the pace of change was not as swift as it is today, but today it is irresponsible to neglect the necessity to revise KPIs frequently and often make them situational. When COVID happened, we witnessed a drastic effect on the supply chain, manufacturing, and retail sectors, requiring revision of the KPIs for the entire value chain of many companies, and we experienced implications of struggles to do so. Looking ahead, we see regulatory initiatives in the space of energy and sustainability, geopolitical risks requiring restructuring supply chains, and the list of disruptions requiring business agility, and therefore, objectives and KPIs revision might go on. [2] Even though KPIs realignment and adjustment is quite an expensive and long process, it is inevitable that organizations will do it more often. And those that leverage the power of artificial intelligence technology that can reduce the transactional cost of realignment will gain a competitive advantage.
The authors distinguished 3 groups of KPIs:
- Smart Descriptive KPIs: These provide insights into what has happened or is happening by analyzing historical and current data. They help understand the reasons behind performance issues, which can lead to better KPI formulation or understanding how different KPIs affect each other.
- Smart Predictive KPIs: These forecast future performance and provide early signals that can guide actions to avoid risks or exploit potential opportunities. These indicators help in quickly and effectively executing strategies.
- Smart Prescriptive KPIs: These not only predict outcomes but also suggest specific actions to take in response to those predictions. They help align various parts of a business, such as sales and operations, by advising adjustments to sales KPIs based on supply chain performance.
Such grouping represents a maturity evolution of the KPI, however, I believe the revision frequency, organization level, and impact of the decision might define the appropriate group of smart KPIs.
When considering the frequency with which KPIs should be revised, the integration of Smart KPIs becomes especially relevant.
For real-time operational KPIs, where immediate feedback is essential, Smart Descriptive KPIs are particularly beneficial. They provide instant insights into ongoing processes, such as website traffic or assembly line outputs, helping to understand and respond to performance issues as they occur.
Periodic tactical KPIs, updated at regular intervals—whether daily, weekly, or monthly—could effectively utilize Smart Predictive KPIs. These KPIs would enable departments to forecast upcoming results and align their actions with the anticipated trends, ensuring that strategies are executed promptly and effectively.
When it comes to long-term strategic KPIs, which are updated less frequently, Smart Prescriptive KPIs could play a pivotal role. By not only predicting future outcomes but also recommending specific responses, these KPIs align long-term strategic objectives with actionable steps, thus optimizing decision-making on a strategic level.
For situational ad-hoc KPIs, a combination of Smart Descriptive and Smart Predictive KPIs may be appropriate. They can provide quick analysis in response to specific events and forecast the implications of such events, allowing for a more agile and informed response to unexpected changes.
At the organizational level, strategic KPIs that reflect the overall goals of the organization would greatly benefit from Smart Prescriptive KPIs. These KPIs could guide high-level strategic planning with their recommendations, aligning various business functions towards common objectives.
For tactical KPIs, which focus on the performance of organizational departments or teams, Smart Predictive KPIs could provide forecasts that bridge the gap between strategy and daily operations, preparing teams to meet future challenges proactively.
Operational KPIs, which are concerned with the day-to-day functioning of specific processes, would find Smart Descriptive KPIs most useful. These KPIs would offer continuous monitoring and analysis, allowing for immediate adjustments and performance optimization.
Lastly, at the individual level, Smart Descriptive KPIs could assist employees in understanding their current performance, while Smart Predictive KPIs might help them anticipate the outcomes of their work, facilitating personal development and alignment with the broader organizational goals.
Without unfolding details, the articles’ authors refer to AI as an umbrella of technologies responsible for the implementation of smart KPIs.
However, I believe it is important to recognize that an organization should have a lot of mature fundamental capabilities starting from cloud and infrastructure, data management, data engineering, data science, simulation, and modeling all the way to digital twins, which is the key enabler of the smart KPIs.
The concept of a digital twin of an enterprise [3] and its operating model stands as a fundamental enabler for the deployment and effectiveness of smart KPIs. Such a digital twin acts as a comprehensive virtual replica of an organization, encompassing its processes, systems, and dynamics. This virtual model is integral to the realization of smart KPIs, as it provides a detailed and dynamic environment in which data can be analyzed, scenarios can be predicted, and strategies can be tested without disrupting actual operations.
In the context of smart KPIs, the digital twin serves as an advanced simulation platform where Smart Descriptive KPIs can be observed in a controlled environment, enabling a deeper understanding of the intricate interplay between various organizational components.
Smart Predictive KPIs can leverage the predictive capabilities of the digital twin to anticipate future scenarios and their impact on the organization. This allows for the formulation of strategies in a risk-free setting, where predictions are based on a rich simulation of real-world conditions and dynamics.
Moreover, Smart Prescriptive KPIs can be optimized within a digital twin, as it allows for the modeling of complex cause-and-effect relationships and the assessment of various action plans. Here, the digital twin provides a strategic foresight tool, helping to refine the recommendations made by Smart Prescriptive KPIs, ensuring that the actions suggested are not only theoretically sound but also practically viable within the simulated parameters of the digital representation of the organization.
The digital twin serves as a critical infrastructure for application of smart KPIs, fostering a more responsive, agile, and intelligent enterprise.
We encourage you to explore VSOptima the unique digital twin platform that enable your organization to embrace smart KPIs. Reach out to us if you have any questions on the process digital twin implementation or want to explore VSOptima platform. Schedule a call today!
Author: Pavel Azaletskiy
- David Kiron, Michael Schrage. “Strategic Alignment with AI and Smart Kpis.” MIT Sloan Management Review, 5 Sept. 2023, https://sloanreview.mit.edu/article/strategic-alignment-with-ai-and-smart-kpis/
Michael Schrage, David Kiron. “Improve Key Performance Indicators with Ai.” MIT Sloan Management Review, 11 July 2023, https://sloanreview.mit.edu/article/improve-key-performance-indicators-with-ai/
Kerremans, Marc, and Tushar Srivastava. “Market Guide for Technologies Supporting a Digital Twin of an Organization.” Gartner, 13 July 2021, www.gartner.com/en/documents/4003512.