How Data-Driven Capabilities Enable Smart Organizations
Moving past buzzwords and hot trends toward a capability framework will lead to smarter operation. It all starts with what it means to think in capabilities.
Introduction
This article is the first in a series in which I will introduce and explore a capability-based framework that describes how data, analytics, activities, and controls can be effectively combined to enable smart organizations. Capabilities define what organizations must have the capacity to do to achieve superior results.
To use this framework, your organization must identify and describe what capabilities are required to achieve its objectives. Capabilities enable other capabilities and form a network that ultimately accomplishes the desired outcomes you are working toward.
Historical Perspective
The need for information to run a successful organization is not a new concept. However, during recent years there has been a major shift in how the value of information is understood and how it can contribute in new ways to overall success.
Several waves of progress have been made in how companies acquire and consume information. Macro trends such as lower technology costs combined with higher capacities and mass connectivity have been transforming the economy and how commerce is conducted. However, the pace of transformation is accelerating with the recent growth of smart phones, social media, and sensors of all kinds.
The availability of data is now characterised by the big-data hype cycle. Society has transformed into a digital world with immediate access to a wide range of data that keeps us informed, provides entertainment, guides our journeys, enables commerce, monitors our health, and generally keeps us connected. The impact of this digital transformation has been disruptive and has created major opportunities. There have been winners and losers.
A major challenge facing organizations today is how to identify new business opportunities during periods of major change without being distracted and consumed by hype, noise, and confusion.
Managers are constantly searching for new techniques to improve their organizations. During the past several years, many techniques and approaches have been considered; there has been no shortage of good ideas. Examples include:
- Total Quality Management (TQM)
- Six Sigma
- Enterprise performance management
- Business process management
- Business process reengineering
- Lean manufacturing
- ISO management systems
- Enterprise risk management
- Enterprise architecture
- Customer relationship management (CRM)
- Activity-based management
- Information engineering
- Data warehousing
- Business intelligence
- Data analytics
- Data science
Some of these techniques have delivered compelling results. Others provided disappointing results and were abandoned. Some techniques are process-centric, others are data-centric. Some techniques depend heavily on analytics. All of them are intended to help organizations improve their performance. They presume that a smarter organization that is well resourced and highly motivated should produce superior results.
The fact that the above list is lengthy is part of the problem. The list of new techniques is continuing to grow rapidly due to innovation and new ideas. There are overlapping ideas and concepts that span many techniques that may cause political and ownership issues when an enterprise tries to implement them.
Management fads come and go. Technology fads come and go. However, there are strong, underlying trends that need to be separated from the fads. Some techniques will gain traction and provide elements of success for varying periods of time. Each technique noted above has the potential to be successful, but there are organizational reasons why some techniques succeed in company A but fail in company B.
Disappointing results are typically related to silo-based thinking, incomplete solutions, missing or limited skills, competing and overlapping approaches, confusion and poor understanding of the required commitment, and a lack of accountability for success.
Competing approaches can arise because of where various improvement techniques came from. Consider that there are separate groups within most firms based on information technology, finance, and operations. Historically business intelligence came out of IT, enterprise performance management was sponsored by finance, and Six Sigma commonly came out of operations.
All three of these approaches are, or should be, based on measurement, analysis, feedback, and improvement. However, many organizations view these disciplines as separate, competitive, and distinct. In broad terms, each silo is attempting to address similar issues but they are viewed as competing with each other, leading to disappointing results.
Taking a Capability View
The new concept that should be introduced into this discussion is capability. It was defined earlier in this article as the capacity to do what needs to be done in order to be successful. Capabilities allow the conversation to rise above organizational silos and identify what specific actions we need to be capable of.
Adopting a capability view helps reduce confusion related to hype and the impact of new buzzwords and terminology. For example, rather than being caught up in endless debates about implementing data in the cloud or on premises, a capability-based discussion shifts the conversation to focus on the ultimate business capability that would be enabled by either approach.
Effective decisions can be made by considering technology options within the context of required business capabilities. Discussions can be carried out based on shared objectives. Team alignment is a valuable result of adopting this approach. The rapidly evolving landscape of data, analytics, and technology can be monitored and understood by a diverse set of people because they share a common perspective.
It is important for us to shift our thinking and conversations about how new ideas and improvements are implemented. We need to shift our approach away from implementing a series of "things," such as databases, software, dashboards, reports, and predictive models toward describing what capabilities we are trying to enable.
Evaluating how well we are able to execute a capability defines our competency. Because capabilities describe what we need to do, competencies describe how well we do it. Taking a set of capabilities that we agree to and evaluating our capacity to exploit them based on our competencies will identify any gaps we need to address.
A capability can be considered to be an organizational "building block." Lower-level capabilities are assembled to enable higher-level capabilities. Each capability is composed of four elements: skills, processes, technologies, and policies. They define the ingredients necessary to implement the capability in an organization, and form the design basis of how to build or develop a capability.
The skill component of a capability describes the human element that includes knowledge, motivation, experience, and attitude. The process component describes the activity used to enable the capability. The technology component of the capability includes information, computing, storage, communications, and automation elements. The policy component includes the standards, best practices, enforcements, and governance elements needed for each capability.
Taking a capability view allows us to determine if all of the necessary components are in place to enable it, or to identify if any components are missing. A capability view allows us to connect lower-level capabilities at the individual level to form team and enterprise capabilities at a higher level.
The next article in this series will introduce the capability-based framework and describe its major components.
About the Author
Mark Peco, CBIP is an experienced consultant, educator, and team builder. With graduate and undergraduate degrees in engineering from the University of Waterloo, he helps clients identify and build the necessary analytics capabilities that will drive business impact.
As a leading practitioner of business intelligence and analytics, Mark is a faculty member of TDWI and teaches companies on a global basis how to implement and govern “intelligent” business solutions. He is CBIP certified at the mastery level and maintains his professional focus at the intersection of business, operations, and technology. Mark has several years of energy industry experience based on a variety of roles in the pipeline, distribution, and production sectors.
Mark lives in the Toronto area and can be contacted at [email protected].