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Kimberley Reed Written by Kimberley Reed
on 08 Oct 2020

As a product owner designing and delivering software solutions for utilities, digital engineering brings us new opportunities to be innovative in our solutions. Working in partnership with our customers and drawing on their knowledge base gives us confidence that the end solutions we deliver will benefit them.

From my perspective, three core elements are driving our success and growth in digital engineering:

Partnering and collaborating with customers and end-users

Gone are the days where a software development company wins a project and delivers exactly what is in the proposal, with any exceptions needing to go through formal change control. Now we are working in partnership with our customers, often using an agile methodology, including interactive workshops, to really understand their requirements and design the solution together dynamically. We see the best results when we are transparent with our customers, keeping them involved in the development process, including providing access to the solution that is being developed, while staying flexible and open to re-prioritizing features based on customers’ needs.

Making decisions based on good quality data

Data has often been overlooked in this process, moved to the “too hard basket,” or said to be “another team’s problem.” As digital engineering evolves, we are starting to see the tangible benefits of investing in data. We are seeing a shift where data is increasingly treated as an asset to the organization. We use data to help make informed decisions or to identify solution requirements along with preparing and validating solution models. Within projects, we are now starting conversations around data at the beginning of the project. Before using data for a new solution or model, we often use our position of being outside the organization’s day-to-day business decisions to provide an unbiased assessment of the organization’s data maturity against ISO 8000-61. With these results, we can identify if there are any data issues (process and quality) that need to be resolved at the organizational level before we progress to solution development.

Removing silos and creating end-to-end solutions

To successfully deliver end-to-end solutions, we look at all areas that our solution will cover. The key to this is to understand and prepare the input data (not only for our solution, but for other solutions/platforms that may benefit from it), and then, to review automation and business intelligence opportunities. Our partnership with our customers enables us to conduct workshops with all stakeholders so that we can design a product that will not only consider the immediate requirements, but also future-proof it.

The combination of these three elements has been vital to my team’s success. We work closely with our customers, interacting regularly and involving them in the entire process. In the utility industry, we often design solutions that consume data from multiple input data sets. We run initial workshops to understand the problem statement and to identify all stakeholders. We further review the input data and if required, conduct an independent data maturity assessment. Once this is completed, we work with our stakeholders to help design an end-to-end solution that often results in cross-departmental advantages.

What next?

As an industry, we are seeing promising growth in both partnership with end-users and the removal of silos. However, I think we still have some way to go in making data-driven decisions. As we help more companies understand the value of investing in data and implementing organization-wide data process strategies, we will open the doors for creating innovative automated solutions driven by business intelligence.

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