Current state assessment: the first step towards effective data management | Logic20/20

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Current state assessment:
the first step towards effective data management

“You are here.” If you’ve ever had to navigate your way through an airport or convention center, finding these three words on a map are the first step in getting where you want to go.

 

When utility companies set a goal of getting a handle on their data and using it more effectively, the journey towards that goal starts with the same step as the airport scenario: figuring out where their data ecosystem stands today. We call this step the current state assessment (sometimes called current state analysis), and if it sounds like simple common sense, it is. But you’d be surprised how often businesses get it wrong … or leapfrog right past it.

 

When a utility approaches current state assessments from a holistic perspective, evaluating every relevant aspect of their present situation—the good, the bad, and the ugly—they have a solid foundation for the strategy that will drive them towards their goal of effective data management. Along the way, they often learn some surprising insights about root causes of the misalignments they’re trying to address.

 

Today, we’ll discuss how to do a current state assessment as a first step towards effective data management.

 

 

When a utility approaches current state assessments from a holistic perspective, they have a solid foundation for the strategy that will drive them towards an effective data ecosystem.

 

 

Why current state assessments are necessary 

Whether your goal is finding an airport gate or building a structured data ecosystem, the first task is the same: finding the “you are here” point. Knowing where you are today gives you a clear picture of how far away your goal is and lets you begin planning a path to get there—without unnecessary detours that can waste time and resources.

 

In many organizations, there’s a strong temptation to skip this important step and move straight into planning solutions. But without a current state assessment, they risk misdiagnosing the root cause of data misalignments and heading down a wrong path, only to later discover their error and have to retreat back to Square One. In addition, the oversight of one or more critical issues could lead to designating a future state that has little if any chance of success.

 

For example, if the problem is lack of data alignment across the organization, it may be tempting to launch a comprehensive strategy for upgrading servers and integrating new data management tools. But if the root cause is actually haphazard data classification and data indexing, achieving the goal requires a very different strategy.

 

While the need for a current state assessment may seem like a no-brainer, we often hear from clients about consulting firms who bring in cookie-cutter data management solutions without bothering to evaluate the problem at hand. When we work with clients, we take the time to build a 360-degree picture of the present data ecosystem, which enables us to identify the issues with the greatest impact on ROI and assign them top priority when we build the strategy. To some our approach may seem “old school,” but time and time again it’s proven to be an investment that pays off many times over.

 

 

Without a current state assessment, utilities risk misdiagnosing the root cause of data misalignments and heading down a wrong path. 

 

 

Where current state assessments can go wrong

In addition to skipping them entirely, a host of other errors around current state assessments can delay or even derail progress towards a the goal of effective data management. Here are a few of the biggest hazards to watch out for.

 

Settling for a superficial understanding

A utility’s strategic problems are rarely simple, so giving short shrift to the current state assessment is likely to lead to wasted time and resources down the road. Reviewing a few reports and talking to a couple of executives will rarely yield the kind of insights needed to determine and implement a course of action with confidence.

 

Ignoring cultural aspects

Another potential pitfall to avoid is relying solely on quantitative data or on the high-level perspectives of department leaders or process owners. Aligning data across an organization involves change, and every major change involves people at multiple levels and in multiple roles. Understanding the cultural aspects of a problem is key to building a strategy that everyone can support.

 

For example, if the business is addressing low adoption rates for a data warehouse application, one of the key causes could be insufficient or poorly designed training for the desired users—a factor that might only be uncovered by involving the users themselves in the assessment process. Bringing users into the process at the assessment phase helps ensure a solution that works at all levels.

 

Over-reliance on surveys

Surveys are simple, easy to create, and capable of collecting data from hundreds of individuals with relatively little effort. They do not, however, provide all necessary information to plan an effective strategic roadmap towards efficient data management, and they lack the personal connection needed to give stakeholders a sense of ownership. When we do a current state assessment, we conduct personal interviews with stakeholders at all levels (in person or virtually) to gain a thorough understanding of their perspectives on the issue, their concerns, and what they need from the solution—insights that surveys alone can’t deliver.

 

 

Avoid the pitfalls: get the whole story, understand cultural aspects, and conduct personal interviews

 

 

5 steps to a successful current state assessment

We’ve developed a five-step approach to ensure that every current state assessment we conduct for a client is accurate, thorough, and robust enough to serve as an effective foundation for the project. If you’re looking for a current state assessment template, this is a great place to start.

 

The 5 steps of current state assessments: collect, assess, socialize, synthesize, and realize

 

1. Collect

First we collect all relevant information about the data ecosystem via surveys, documentation reviews, and interviews with stakeholders at all levels. Then we document all our findings regarding operating models, processes, and high-level roles and responsibilities.

 

2. Assess

In this phase we create a high-level operating model of the desired data ecosystem, including roles and responsibilities, conduct a gap analysis between current state and future state, and develop a hypothesis for remediating the gaps.

 

3. Socialize

Now it’s time to bring in our stakeholders, share what we’ve learned, and collaborate on next steps. We conduct meetings with core stakeholders where we report our findings and hypotheses from Steps 1 and 2. We then review the proposed data ecosystem, incorporate key changes based on stakeholder feedback, and finalize for roadmap planning.

 

4. Synthesize

Here’s where we refine our proposed solutions and recommendations. In this step we also do something that often surprises our clients: we expand on our recommendations to include practical to-do items and best practices. This ensures that the client would be able to drive actions to achieve the desired results on their own if they choose to do so.

 

5. Realize

We wrap up the assessment process by creating next steps and building a roadmap encompassing people, process, and technology to realize the data ecosystem enhancements we identified in our recommendations.

 

Abraham Lincoln once said, “Give me six hours to chop down a tree and I will spend the first four sharpening the axe.” In solving a business problem or pursuing a goal, the current state assessment is the equivalent of a good axe-sharpening, providing the insights needed to build a laser-targeted roadmap and set off on the right foot. Take the time to do it—and do it correctly—and you’ll be well on your way to an accelerated journey towards effective data management.

 

 

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