Why Many Companies Fail When It Comes To Monitoring
Most organizations that fail at operationalizing their monitoring objectives do so because their teams are not aligned within the enterprise. Some teams concentrate on basic, straightforward data collection, visualization, and documentation. Alternatively, other teams are more advanced in their data collection, yet may be unnecessarily intricate and require lengthy implementation for solutions, which can be difficult to improve upon once established.
The majority of monitoring systems are incapable of providing scalable solutions for regularly aggregating results from distributed environments. Those that do may necessitate extensive customization or manual data aggregation.
So, without further ado, here are the eight most common monitoring system mistakes to avoid:
1. Monitoring and evaluation is a luxury
This misconception cannot be further from the truth! In the field of social effect, there is a myth that impact monitoring is a luxury and a necessary evil to appease a stakeholder.
2. Lack of data trust
To increase stakeholder-aligned impact, this process necessitates a culture of impact and result alignment, a better language of impact assessment, and agreement on enhancing data culture. This is the single most overlooked reason for a lack of data trust, as well as the most egregious waste of valuable resources.
3. Missing theory of change driven data collection
Data collecting is either non-existent or lacks a solid data strategy in the majority of organizations. When they do collect data, they frequently focus on activity and output metrics, which rarely match or confirm the organization’s fundamental mission and vision. The major hurdle to understanding social change is the absence of alignment between the theory of change and data collecting. An organization cannot understand WHAT, WHO, CONTRIBUTION, HOW MUCH, and RISK without this alignment – a critical prerequisite of understanding and communicating
4. Data islands and rudimentary data aggregation
To better understand application, the data collection system aligns with the change-based approach theory.
- Where do you collect activity and output data?
- Are these data complete?
- What is the core outcome that you seek to achieve?
- How do you know if you are making the right kind of change?
- How can you aggregate results and learn valuable insight in a short time?
The challenge here is that most organizations data collection and program management data system is all over the place.
5. Weak impact framework is a barrier to demonstrating the impact
While there are numerous frameworks – result frameworks, effect frameworks – available, based on the organization’s role, we will most likely begin with one of them and change it to match internal objectives. The finest framework is one that frequently aids in the alignment of various participants in the impact ecosystem. However, where do you begin today?
6. Lack of stakeholder’s (can be the Infrastructure team, Network team, etc.) voice in measuring impact
The primary purpose of impact measurement is to drive a better outcome for the end users. However, do they have a system / process that communicates user experience or satisfaction or dissatisfaction to all stakeholders?
7. Communicating impact to vendors is difficult
The most significant barrier for vendors is a lack of visibility.
8. Custom vs. configure
Customization is expensive, non-flexible, time consuming, and complex.
Together we are on a mission to make impact measurement and management simple for everyone.
Regardless of where you’re at along the monitoring / observability maturity curve – OR – how much of a hole you think you need to dig out of, the pace of change and increased complexities that need to be understood and managed across IT will only make the hole wider and deeper.
Any major IT initiative (Cloud, devops, automation, etc.) needs to have a monitoring strategy at its foundation. It’s a natural segue to make the necessary monitoring improvements that will allow for easier and faster success to desired end state. This doesn’t mean just get a new shiny tool that shares similar buzzwords as your initiative. It means rethinking the people and processes that surround it. Don’t fall into the old habit of it being an afterthought.
The approach and methodologies to overcome these barriers aren’t rocket science, but do take a concerted effort to upend. It all starts with having the right game plan and actionable playbook to execute from. It’s incremental steps in the right direction that yield the biggest gains over time.
The Evolving Solutions Enterprise Monitoring & Analytics Practice has invested heavily in monitoring / observability experts, allowing us to help large enterprise customers with the products, people, and processes. This enables organizations to unlock answers from the data and accelerate their business transformation.
The relative effort of input of correcting your past deficiencies in monitoring far outweighs the positive downstream output and is what is critically needed to meet the demands of today’s consumers. To discuss further, feel free to reach out to our team at email@example.com.