Key Technologies Supporting Goals

There is a significant emphasis on managing goals and their interactions in today's demanding business world. Today’s goals are not only stretch goals, but they also often appear to be at odds with each other and out of touch with stakeholders' needs. Financial goals which are picking up steam seem to be at odds with digital progress. Savvy organizations balance these goals by focusing on managing goals in real-time and leveraging vital technologies to attain these goals. This post will describe how these key newer technologies support the Goal Life Cycle (GLC) and better goal management. Remember that these are the more modern and effective technical supports for goals. For many decades, most organizations have been limping along with traditional presentation tools and spreadsheets. These conventional tools still contribute to goals but lack the high speed and connected visibility essential in today’s changing business environment.

Collaboration Tools

Collaboration tools have been on fire recently because they speed up communication uniquely. They can support group collaboration, and everyone can either point to or attach content. This real advantage in supporting the GLC, and any adjustments necessary in goal attainment can be communicated rapidly. The problem with random communications that are really fast is that they can inundate the receivers and create distractions. A new variety of goal-focused collaboration tools are gaining momentum as all communications are linked to stakeholders and high-value goals through dynamic repository-based goal models. They are called goal-lead communication tools, and they cut through the noise while adding excellent visibility to all participants.

Case Management

Case management really focuses on goals and milestone attainment rather than activity sequences. Mostly case management is about reaching goals, but it is also rich in information about why specific goals are not being completed. This information can play a crucial role in adjusting goals or identifying anomalies that require innovation and thought. Exceptions are handled well in case management, and it coordinates the appropriate people and systems to act correctly to reach goals.

Low Code

Low code is a way to abbreviate program coding and open the programming world to those who are not tech-savvy. Often a model-driven or drop-down menu approach to creating processes, action steps, and microcode. Low code delivers a faster reaction to underlying processes, and code changes when goals change. Many process and workflow technologies practice the low code approach run by business professionals.

Data Mining

Data mining is a crucial way to watch the physical world of actions/data, and content to adjust goals in the GLC. While real-time mining might adapt the execution of an action in flight, its contribution generally revolves around finding patterns that may require new steps. Mining can involve data logs, extending to content live images, voice, and videos. Mining can handle raw data in context, but it can also reach to add analysis and learning.

Explicit Rules/Parameters

Where goal volatility or conditional action can be anticipated, many application developers depend on rules, parameters, and boundaries outside the system of execution. Goal changes imply changes in rules that can be changed immediately to alter new targets. It helps in delivering the attainment of dynamic or emergent goals. It also enables speedy adjustment to goal changes.

RPA

Robotic automation is a great way to create low-cost and speedy attainment of known goals. They tend to be well-worn paths, but they are closely watched for tolerance variation that could imply reaching for new adjustments in plans and stakeholder visibility. As more intelligent bots emerge and evolve that are data, AI, or algorithm-driven, RPA will create more transparency touchpoints and suggestions for goal adjustment.

AI

Today AI is rich in learnings that can potentially point out the need for goal adjustment and new goals to pursue. AI, as it evolves, will sense, decide and act more proactively, assisting management with the GLC and maybe dynamically automating part of the process to get better goal attainment performance. The roundtripping from learning to changed actions is an area for rich future development for AI.

Net; Net:

While each of these technology supports for the GLC and goal attainment was described in a categorized fashion, we will see savvy organizations and vendors combine multiple siloed technical supports into powerful combinations and even Digital Business Platforms (DBP). Goal collaboration platforms will emerge to lead in the development and maintenance of goals that drive business outcomes that adapt to change and even business scenarios.