Data is everywhere. There is data inside our organizations and outside. Some data is in the form of measurements. Measurements can be descriptive, predictive, or for diagnostic reasons. In either case, we measure to make decisions based on the quantity and quality of something. Measurements can give us actionable operational, tactical, and strategic metrics for influencing human and artificial decisions. Organizational experts at every level, besides just using their opinionated industry expertise, also rely on data to enhance their decisions.
This leads to challenges with what data to collect and how to use it effectively for specific outcomes. Collecting data is the easy part; integrating and orchestrating data collaboration across a value chain is the hard part. Every functional unit uses different tools, automation, and manual interfaces for performing their job across a chain of interconnected activities for producing a service or product for the organization. In many cases, data analytics are siloed within a function or require manual people-oriented exchanges between functions in the organization. Data needs to be integrated, without being constrained by organizational boundaries for people, processes, and technologies to effectively harmonize.
If data, information, and knowledge interchanges are not done with strategic intent, we risk ineffective organizational collaboration and poor use of our assets. This can cause challenges with decision making in an organization at every level. Data and information do not move in one direction across an organization’s value chain of activities, but there should also be a feedback mechanism through the use of data exchanges to help organizations be more agile and precise in how they use and interpret information for strategic, tactical and operational intents.
Data transforms into information, information into knowledge, and knowledge into decisions. This is the DIKW model. Information systems need integrations at various levels, across various tools and technologies to enable informed, precise decisions across the organization.
When transforming data, consideration needs to be given to how to transform measurements into metrics and metrics into key performance indicators. Key performance indicators (KPIs) take data metrics and help an organization focus on what matters the most. The KPIs should be related to critical success factors (CSFs) for each organizational objective or project. Each organizational objective should relate to the strategic intent and investment strategy of the organization. As these data elements are connected across the organization, visibility from strategy, tactics to operations can be achieved.
Fully integrated and automated heterogeneous systems expedite data exchanges, workflows, and decisions for people, including artificial intelligence-enabled technologies. This helps all business processes perform better and improves forward and rearward visibility for agility.
Data and Business Strategy, Tactics and Operations
Some business strategy concerns are usually related to decisions that affect the return on investment (ROI), value of investment (VOI), and total cost of ownership (TCO) of the organization’s capabilities and resources for delivering and supporting the portfolio of products and services to the market. These financial concerns affect the performance of the entire organization, including influencing the budget for innovation, providing customer-requested enhancements, customer fixes, and competitive features. Each of these areas has strategic intent and receives a portion of the budget for execution.
Most organizations decide business strategy investments for a year and then review their decisions at year-end for modification of the next year’s decisions. Although the organization may have a multi-year vision and mission established, this is usually the case, especially for managing the budget investments.
Using agile tactical and operational feedback across their service value chains can modify or shift the budget spend quickly based on data feedback integrated into their business systems, quickly affecting the top line and the bottom line in their organizations. Daily monitoring, watching trends, environmental issues, the success of tactics, and production of operations across the organization is enabled with organizational-wide integrated data, information, and knowledge.
Improving Business Outcomes
In today’s highly competitive environment, decisions must be made quickly to improve the long-term viability of the business. Information superiority for competitiveness is a necessity. Actian DataConnect simplifies data integration across the organization. Offering them the strategic ability to answer the following questions and more using data-rich metrics instead of just people expertise.
- Where are we now?
- Where do we want to be?
- How do we get there?
- Was the change effective?
- How do we measure our progress?
- Are resources and capabilities being used effectively and efficiently?
- Are there any constraints?
- Is the current strategy and tactics effective?
- Are operations working effectively, efficiently, and economically?
Technology, data integration, people collaboration, and communication go hand in hand. To improve results and overall business outcomes, organizations must work as one, sharing data and information seamlessly to support strategic intent, programs, projects, and overall successful operational decisions. Enterprise data integration improves the business overall, including customer expectations and experiences.
Actian DataConnect provides the technology platform you need to achieve your Enterprise Data Integration objectives. Through a highly scalable hybrid deployment model, robust integration design capabilities, and automated deployment capabilities – DataConnect can help you deliver more effectively and faster than other solutions. To learn more, visit www.actian.com/dataconnect.