The ValueWorks model company approach

How our valueworks.ai model company approach can help you to win back full oversight over your company data

We at valueworks.ai strongly believe in living what we preach. Therefore, we consider ourselves as “customer zero”, where our team plans, reports and executes using our own valueworks.ai solution. This includes mimicking the system landscapes of our co-innovation customers and enforcing process best practices developed with subject matter experts, e.g., for Salesforce. As a result, by leveraging our internal model company we can support our customers in two ways:

  • We can help our customers to set up or transform their system landscape in line with best practices and win back full oversight over their company 
  • We “double-test” new releases to ensure the highest quality and user experience standards.
Our valueworks.ai model company enables us to help customers get up to speed quickly while also providing us with a valueworks.ai-internal learning environment that mimics the system landscape of our customers.

Figure: IT system Landscape

Starting point: It is common knowledge that IT system landscapes can be tremendously complex with steadily declining data quality. In this situation, there is a strong tendency to stay in a “comfort zone” and manage data in silos within the transactional systems itself. We believe that your company loses valuable insights by doing this. While we are aware that gaining back oversight over your data is not an easy task, we believe that by:

  • Setting up your systems correctly with a cookbook-approach, and
  • implementing our proven valueworks.ai solution, you can achieve just that.

The model company focuses on the first part, namely setting up your IT landscape correctly, by answering the following questions:

  • Which are the right systems for my company phase?
  • How should we set up these systems from a process perspective in order to adhere to best practices?
  • How do we ensure correct user behavior to establish and maintain high data quality standards?

Based on this, the benefits of following our model company approach are simple. Depending on the company phase you will be able to:

  • Define a system landscape and best-practice processes to avoid extensive customization which will in return enable automation
  • Integrate data sources in a “self-service” data-mapping approach that will help you get up to speed in a fast manner

Figure: How the model company approach streamlines valueworks.ai JUMP Start method of integration

Guidance on system landscape: At valueworks.ai we have done extensive research to understand the requirements and best practices of the IT system landscape in various domains: Finance, HR, CRM, Marketing, etc. Based on this and the experience from our co-innovation clients, we have defined a target system landscape that we would suggest and which has the potential to accelerate your growth significantly. Selecting the right systems has various profound implications on the data side, impacting the transparency you can create throughout your company. For example:

  • Seamlessly integrate data without Excel imports
  • Access all relevant data fields easily
  • See how easy or difficult it is to reflect best practice business processes in your organization

Best-practice (business) processes: There is a high interdependency between choosing the right system and then having the capabilities to configure it optimally. Once the system has been selected, valueworks.ai provides you with a “cookbook” that helps you to set up the system from a technical, administrative and user perspective. Our model company approach ensures that the systems are then implemented correctly to get the most out of your company’s data by leveraging valueworks.ai.

User behavior and training: The final component is the user behavior. We all know too well that as a matter-of-fact user behavior is the number one driver of “bad data quality”, as it requires a steady discipline to go the “full way”, when shortcuts sometimes seem to be the easier way. Working with our customers, we have found ways to enforce safeguards and mechanisms that ensure high data quality. This can be either on the system side, where certain workflows are implemented, or also through training and making it crystal clear to users, why they need to follow predefined procedures. Motivational research has again and again shown that understanding the purpose of certain tasks raises adherence to the established task protocol significantly.

At valueworks.ai we want to help you win back oversight over your company data.

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