Data silos can cause inefficiency and ineffectiveness, but creating a strategy that promotes wide-scale analysis over large-scale storage, organizations can truly understand and easily use their data.
It’s the age of big data, which means just about every business and organization under the sun is stocking up on massive amounts of it. What's worth noting, however, is that a shocking 88 percent of what’s being collected is never analyzed.
A major contributor to this trend is siloed data — where one department “owns” certain information and keeps it isolated from the rest of the organization. Like grain in a farm silo, this data is closed off from all outside elements.
Data silos have both technical and cultural origins. On the technical side, enterprise resource planning (ERP) and other legacy software applications store tons of business information, yet their designs make it challenging to use the data in any actionable way. Culturally, though, we are seeing a big push toward data transparency, departments struggle to find the easiest and best ways to share their findings with others.
Data silos can impact an entire public-sector organization, but three areas in particular hurt the most.
Budget Planning: Budgetary data silos typically result from the limited amount of insights organizations gain from ERP application reports and traditional Excel spreadsheets. The finances of the past year tend to be presented as a simple summary of budgeted spending versus actual spending. When this is all departments see, they don’t truly understand how or why dollars are being spent, and they don’t know how to properly plan their budgets for the next year.
Information Technology: Data silos place an especially heavy burden on IT staffs. These are the people who end up being tasked with maintaining siloed systems, managing the growing infrastructure of data, and putting that data to use. IT departments are often understaffed and working on shoestring budgets as it is, so dealing with data that is siloed across the entire organization only stretches them thinner than they already are.
Human Resources: With a limited view into siloed data, HR can only realistically access and use a small portion of information about its organization’s workforce. This makes it particularly difficult to analyze employee engagement, prevent unexpected departures, and prepare succession plans (something that’s especially important these days, given that a large portion of the public sector’s workforce is set to retire within the next five years). Each of those people’s succession plans will impact many aspects of an organization, from strategy alignment to payroll to benefit costs. Without access to the full picture of data, it becomes challenging for HR to plan accordingly.
To unlock your data, develop a master data strategy; something that might seem difficult if you’re a small to mid-sized organization that doesn’t have a robust budget or large amounts of resources.
However, several affordable technologies exist in the market that come prepackaged with capabilities that address the public sector’s exact data reporting needs. Many of these solutions can automatically sift through siloed data, identify the relevant insights, and transfer them to a centralized platform (oftentimes, one that is cloud-based.) Ultimately these tools help organizations eliminate bad data and store their good data in a fashion that makes it easy for everyone to analyze and base decisions on.
As an example, one county government I work with was struggling to understand its workforce’s overtime trends because its payroll information and timekeeping were stored in two completely different systems. However, once it embraced a cloud-based reporting software solution that combined the data to analyze trends, the county was able to more easily identify its payroll patterns and better budget and plan for the future.
In order to see positive results like that county did, it’s important to take the following four steps:
1. Conduct an application-reporting inventory. Identify all of the different business applications currently being used throughout your organization, as well as where opportunities exist to consolidate and share information across departments through a common view of the information (regardless of where it’s stored). We’ve learned that many organizations are having to dump data into Excel, and consolidate and reconcile their businesses in spreadsheet.
2. Ask the question. Operationally we must have access to report, audit and reconcile, and it impacts our decisions on how dollars are being spent on service-driven outcomes. Today, this is currently a manual, Excel-based or paper process that, if consolidated into one source or warehouse of data, could increase actionable insight.
3. Think historically. When migrating your data to a new system, you need to do some deep thinking about how much historical data your organization truly needs. At the end of the day, data is only of value if it’s current and relevant. You need to be comparing apples to apples in your analysis, so don’t be afraid to leave behind data that might be skewed by external elements, such as economic factors.
4. Prioritize finance and HR. Walk before you run. Begin with your financial and workforce data. At the end of the day, money and people drive almost every major decision an organization makes, so it’s important to have this information readily available as soon as possible.
Data silos can cause an organization to be inefficient and ineffective because team members aren’t seeing the full picture of their data. However, by creating a strategy that promotes wide-scale analysis over large-scale storage, organizations can do more than just collect information; they can truly understand data and easily use it to find internal efficiencies and improve their abilities to meet their strategic outcomes.