Implementing a Proof of Concept (POC) Approach
Many c-suite executives are perplexed at the amount of money their organizations spend implementing and integrating data and software applications with limited evidence that they will even align with desired business outcomes.
A good way to avoid those high costs and solidify the effectiveness of those applications would be to incorporating a Proof of Concept at the inception of the decision-making process. The practice of harnessing all of your organization's data and turning it into enhanced insights requires the right people, processes, and technology, which should be proven with a carefully planned proof of concept to demonstrate how all the pieces of the puzzle fit together.
Often, organizations overlook Proof of Concepts (POC) when seeking to improve business processes. Think of it this way, would you purchase a new car without test driving it first? Of course not! You want to make sure that the car's performance and options meet your specific criteria. The same logic should be applied when deploying data warehousing, business intelligence (BI), and analytics tools. These implementations can be complex, with several challenges that must be avoided in the process.
Incorporating various technologies to understand which best aligns with your organization's needs will require a proven framework to be successful. By implementing a POC, an organization lowers risks and increases confidence about the expenditure. A POC demonstrates the business value early in the process without requiring an upfront investment in the data and analytics technologies.
The framework of a successful POC should take on these distinct actions:
In the initial step, the project team should define the goals, scope, and timeline expectations of the POC. The project's scope will determine if the proposed solution is addressing the specific business needs, and the timeline will guide the team in ensuring important delivery dates are met. It is important to note that the project team should include key stakeholders from the organization's business and IT groups so that enterprise initiatives remain compatible with technical resources.
We scope the proof of concept in the following steps:
- Identify a Business Challenge
- Collect & Integrate the data
- Manage the data
- Visualize the data for analytics
- Drive Real Business Insights
The next step of the POC would be to develop success criteria to measure if the solution fit is accomplishing its original intent. Therefore, defining the scope at the beginning of the project is vital because now the project team can use the success criteria to measure if the application's performance meets the desired expectation.
At this stage, the application outlined in the POC is ready for the test environment, and every measure should be taken to replicate the organization's actual operational processes. On top of testing the original scope, the project team should also test for "what if" scenarios, representing typical changes that the end-user would request. This will give valuable insight to the organization's business and IT groups at what efforts and costs are associated with change requests.
After testing, project members should evaluate as well as validate the POC by summarizing the findings of the project and measuring them against the success criteria. This data, along with the total cost of ownership and enterprise benefits, should then be applied to a final business case to assist with gaining executive buy-in and, if applicable, the development of a complete execution plan.
Today's business environment emphasizes tight budgets. The POC approach allows the organization to validate technical solutions without the initial investment cost and risk of building a full-scale production system. Now, you can drive off the dealership lot with the confidence that you have made the right decision.
Data Ideology's POC's primary objective is to demonstrate the data and analytics solutions' business value with the client's data. This provides our clients with access to the skills and experience to accelerate their learning curve and apply the technology of interest. It's also a low-cost and efficient way to demonstrate how increased insights drive business results.
At Data Ideology, a proof of concept is a glimpse into what success looks like for a data and analytics program. It's always exciting to watch an organization transform data into a strategic asset and harness its power as a competitive advantage. As the organization shifts its thinking to become more data-centric, it's enjoyable to watch the transformation as it develops into a more data-driven culture.
Increasing the organization's analytics capabilities by leveraging the best practices approach to align business and technical leaders enables success, thanks to a data-driven enterprise's endless benefits. This can only happen with a successful implementation that transforms data into usable information that business leaders can use to plan actions. A POC is a significant first step in the journey to becoming data-driven.
Written by Mike Sargo
Chief Data and Analytics Officer and Co-Founder of Data Ideology
Mike Sargo is Chief Data and Analytics Officer and Co-Founder of Data Ideology with over 18 years of experience leading, architecting, implementing, and delivering enterprise analytics, business intelligence, and enterprise data management solutions.