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The initial stage of the Automation Project Playbook is crucial for ensuring that your automation project is not just a standalone venture, but a strategic initiative that supports your company's broader goals.
Keep reading to learn more about defining measurable goals, selecting relevant KPIs, and establishing benchmarks. Mastering these steps is essential for effectively tracking progress and clearly demonstrating the tangible benefits of your automation project.
You run or are part of a business grappling with inefficient processes, and you've decided it's time to automate them with a digital tool or business application. You have a clear vision for what you want to achieve with this project — now, it's crucial to get this goal out of your head and onto paper.
Begin by jotting down your project goal, ideally after discussions with team members and stakeholders to ensure it encapsulates all critical aspects. This written goal not only clarifies your direction but also minimizes distractions and maximizes the use of your company’s resources.
To effectively set the stage for your automation project, take a few steps back and consider the mission and vision of your organization. Analyze how these aspirations translate into strategic goals, which management further refines into operational goals. Select the operational goal most relevant to your project, and tailor the specific goal for your application around this.
While many leaders believe their companies are strategically aligned, reality often tells a different story. This misalignment can lead to inefficiencies and missed opportunities. By starting your automation project with a clear alignment check, you can avoid these pitfalls and ensure that every aspect of the project contributes positively toward the organizational goals.
Likewise, avoid setting an unattainable goal, as it can demotivate your team, erode trust, and undermine future efforts. Be cautious with the specificity of your goal too: overly narrow goals may only offer short-term solutions to broader issues.
After setting the main goal of your project, break it down into specific objectives. By applying the SMART framework, each objective becomes Specific, Measurable, Achievable, Relevant, and Time-bound, which aids in clarity and accountability.
For example, if your primary goal is to enhance operational efficiency in your manufacturing processes, one specific objective could be to reduce machine setup time by 30% within six months.
By meticulously detailing these objectives and their respective deadlines, you create a clear roadmap for your project, enabling better tracking of progress and adjustments as needed. This structured approach not only drives the project forward effectively but also helps in demonstrating tangible results aligned with the strategic goals of the organization.
Recording the status quo is an essential initial step in any project focusing on improvement. It involves selecting and defining Key Performance Indicators (KPIs), which are quantifiable measures used to evaluate the success of an organization, employee, or project in reaching targets. Effective KPIs are well-aligned with strategic objectives, actionable, and provide clear benchmarks for success.
When selecting KPIs for an automation project, it's crucial to ensure they directly support the application's objectives and the broader strategic goals of the organization. For example, if the goal of your application is to streamline inventory management, relevant KPIs might include:
These KPIs are directly related to the efficiency of inventory management, making them appropriate for assessing the impact of your automation application.
To effectively measure KPIs, follow these steps:
By carefully recording the status quo and effectively measuring KPIs, businesses can objectively assess the impact of their automation initiatives. This process not only confirms whether the specific goals of the application are being met but also how they contribute to the strategic objectives of the organization.
With the KPIs recorded, you can now quantify the results later on in your project. The primary aim here is to be able to measure how the KPIs have shifted from the baseline (status quo) established before the implementation to the performance metrics gathered after the application is fully operational. For instance:
With the baseline and follow-up data, you can perform a direct comparison to see how the numbers have changed. This comparison should ideally show a positive trend toward achieving the set KPIs.
For each KPI, calculate the percentage improvement. For example, if order processing time decreased from 4 hours to 2 hours, this represents a 50% improvement. This quantitative data is crucial for demonstrating the efficiency gains from your application.
As we've previously commented, always align these improvements with the broader business goals of your organization. For example, reducing order processing time may lead to higher customer satisfaction and potentially increase repeat business, directly supporting business objectives related to customer service and sales growth.
Even after quantifying the initial results, continuous monitoring of KPIs is essential to sustain improvements and adapt to any changes in business processes or market conditions. Regularly revisiting these metrics ensures that the application continues to deliver value and supports dynamic business needs.
By systematically quantifying the results of your automation efforts, you not only validate the effectiveness of your application but also establish a robust framework for ongoing improvement and strategic decision-making within your organization.
