Govern by Value: Data-driven Business Excellence

Businessman pressing a Value concept button.The onset of the information age has irrevocably changed the way business activities are conducted, evaluated, and managed. A paradigm shift is happening that requires business managers and executives at all levels to understand that data is an integral asset necessary to attain and sustain Business Excellence.

The MBA lessons of the last century: effective management, business processes, quality systems, intelligent organizations, finely tuned leadership, and more are still driving modern enterprises. This conception of effective management adheres to the industrial premise supporting the idea that if all elements of an organization function well, then the enterprise as a whole will perform well too. While this “cogwheels” model has allowed the emancipation of some of the greatest companies of the 20th century, the availability of digital information has come to defy this industrial logic.

The effectiveness of an organization now relies on the enterprise’s capacity to define business excellence policies, and predicatively monitor business value creation using the enterprise’s most valuable asset: DATA.

In order to thrive in the information age, enterprises must now respond better and more quickly to fast-changing and complex environments. Executives at all levels have no choice but to embrace a new vision of what optimal business strategy really entails.

A Twin Tsunami of Data & Regulations

According to the 2013 data Survey Results from Rand’s Secure Data1, organizations can expect for the coming years an annual data growth between 26 and 50 % of their data volume (the median volume being between 20TB to 50TB). While data volume increases at an unprecedented rate, so does the number of rules and regulations imposed on businesses from both internal and external stakeholders. While this “twin” tsunami of data and regulations hits the corporate world, business administration based on mechanistic management systems and processes becomes incompatible with the speed and agility imposed by the information age. This conventional approach is costly and often takes years to implement. This mechanistic view of the enterprise has to be forgotten and replaced by a completely new paradigm that befits the information age.

A Necessary Paradigm Shift: Govern by Value

The “cogwheels” scheme is obsolete. The evaluation of an organization’s performances cannot be measured by the quality of its “cogwheels”, i.e. people, processes, and tools. The integrality of enterprises’ activities must now be aligned with strategic objectives, business rules and data. Enterprises must now invest in tools that will allow them to acquire the necessary agility to adjust quickly to the high paced changing strategic objectives and/or policies. The increased rapidity and frequency of changes also implies that past performances will fail to guide future decisions.

This new paradigm turns old management practices on their head. Currently, the corporations are concentrating the efforts on the quality of the cogwheels composing the corporate machine and their performance, in which case the corporation performance is measured and governed thru the aggregation of past transactions and their performance (BI Systems). Instead, in the new paradigm, an enterprise will single-mindedly focus on and anticipate the ultimate value it intends to create. This is: Govern By Value.

Measuring Value: Key Value Indicators (KVIs)

The mere presence of a resource in a system does not confirm its pertinence and contribution to an organization’s current objectives. While the volume and complexity of data increase at an unprecedented pace, it is essential to assign a value to each resource in order to establish an efficient and fluid organization and align priorities with the most crucial elements. The Govern by Value approach enacts this systematic “valorization” of data that allows a controlled and efficient implementation of the strategic objectives.

KVIs are numerical indicators expressing the value created by each business function’s transactions. Based on semantic model of “Contextual Polarization”, this process of “valorization” is distinct from the common Key Performance Indicators (KPI) (refer to “Polarization: the contextualization of resources”).

One can understand the KVIs as a ratio between the value to be realized and the potential impact of deviation on each business function’s transaction. KVIs thus illustrate what resources are involved, what is its related output, and how compliant it is with your business rules and policies. Practically, KVIs allow you to anticipate the impact of a non-compliant data asset (e.g. employees, customers, suppliers, and products, etc.) before it actually impacts your business.

This changes everything. The question leaders and managers will have to ask when assessing resource productivity and prioritization has to shift from “is this part performing well?” to “how much does this resource add to the ultimate value creation?”

Instead of building organizations from their constituents to meet our strategic objectives, we will now trace the value creation from the top to enable it at lower levels as needed. The implementation of this approach to driving business excellence has radical consequences. When we can express the ultimate value contribution of each of our resources we are quickly able to determine whether we need them at all and if so, what degree of priority (time, budget etc.) they require. In practice, this approach to resource allocation leads to very different outcomes. To consider the value impact at different levels makes sense, but using traditional tools, it is much harder to achieve.

Key Value Indicators versus Key Performance Indicators

Key Value Indicators (KVIs)

  • Measures current and future value creation of a business unit

  • Drives future-based decisions

  • Enables preventive actions

Key Performance Indicators

  • Measures yesterday’s relatives performance of a business unit

  • Drives past-based decisions
  • Enables corrective actions

Polarization: the Contextualization of Resources

In many enterprises, there has been a lot of focus on optimization of business objectives, data quality assurance, business execution and decision support. Typically these efforts are done at the enterprise level.

Data, business rules, and transactions have to be linked and applied at all the levels of granularity, not only the highest. Each business process gives contextual meaning to data and has its own network of accountability and responsibility. In most cases this is very different from the organizational chart.

The consequence is that the ultimate business transaction or value creation of an enterprise is not the hierarchical aggregate of all the underlying business transactions.

Instead the value is created across a myriad of cross- organizational business processes, accountabilities and data sources. This web is dynamic and evolves with changing contexts and priorities.

These insights proved fundamental to the ability to Govern By Value.

Data Excellence Management System: the Missing Link!

Govern by Value is a leap forward in managing the enterprise in the information age. Its feasibility and implementation hinges on a single challenge: measuring value within the enterprise!

The “Govern by Value” approach has immediate ROI and impact. By prioritizing resources and assets, it becomes clear which data requires attention and which data can be ignored. This changes the data management and quality efforts from a necessary, costly, and time-consuming exercise to a rapid self-funding and sustainable process.

 

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DEMS for Predictive Governance

As previously explained, understanding of each resource’s contribution to the ultimate value creation allows establishment of priority of actions. Furthermore, each manager will have at hand a contextual view of the high priority transaction’s value he or she is supervising. This means that the CFO can ensure data transparency, forecast cash flows, and manage risk with more precision. The CMO on the other hand, can control the retention rate of their customers, the associated sales, and their campaigns with precision. The CEO can even decide with accuracy which is the next investment to be made. Overall, using DEMS enables business executives at all levels to anticipate where they need to focus their energy and resources in order to execute their functions flawlessly and deliver on the promises made to customers and shareholders.

1 Rand Secure Data Whitepaper, 2013 Data Governance Survey Results.

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About Walid el Abed

Dr. Walid el Abed is the CEO of Global Data Excellence (Geneva - Switzerland). Dr. el Abed is an international expert in linguistics and computer science specialized in Computational Linguistics and Natural Language Processing. He holds a PhD in Artificial Intelligence. His research was fundamentally oriented on the proposition of a new model called the Semantic Meta Model (SMM) which led to the creation of a new discipline: “The Data Excellence Science”, introduced and taught by him in several universities around the world. A new science that makes it possible to optimize the interactions between humans and computers. A science at the crossroads of the worlds that uses computer science, linguistics, semantics, didactics, semiology and the automatic processing of natural languages. Based on the Data Excellence Science, Dr. el Abed devoted more than 20 years to the creation of a software capable of answering the vital questions that organizations’ executives and managers have to solve in order to perform their mission in the best way. This software is called DEMS the data excellence management system. DEMS has optimized the artificial intelligence for the digital enterprise and people. Dr. el Abed delivers executive training, seminars and conferences on value-driven governance and data-driven management based on the creation of sustainable value and innovation at the right price. Prior to founding Global Data Excellence Dr. el Abed occupied various executive and management positions in large multinationals (Manufacturing, Supply Chain and Financial industries).

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