Not too long ago spreadsheets were a viable solution for managing company data — even for major corporations. But times have changed. 

The dynamic business environments we work in today create data at a rate unfathomable 10 years ago. This invaluable business asset needs to be constantly recorded, analyzed, categorized and reported back to stakeholders who dictate actions based on its merits. 

Spreadsheets are great, but they can't do it all. 

Who Has Time for Manual Effort?

Let's use innovation management, a top priority for future business growth, as a use case. 

Organizations not ready to make the leap to more sophisticated (and expensive) solutions often tracked early innovation efforts in spreadsheets. Unfortunately for them, the effort needed to retain focus meant these businesses outgrew spreadsheets almost immediately. 

"Many established companies are struggling to keep pace with an accelerating rate of change. As a result, companies needing to stay competitive in the market need to get better at innovation management … and need the tools to help establish this," said BrightIdea CEO Matthew Greeley.  

This degree of organization is crucial as Greeley added, "Over 60 percent of programs lose their funding within the first 3 years because they weren’t able to show measurable outcomes from the innovation program."

The management and preservation of innovation data in particular requires agile and efficient solutions that ensure information is created, captured, distributed and consumed in the most effective way possible. Traditional data management systems — case in point, spreadsheets — fall way too short to be relied on for timely, actionable insights.

Data is More Disparate

Innovation data is just one of the many kinds of data organizations must manage. Some of this comes from traditional sources like databases, spreadsheets and other enterprise applications while other information comes from new sources such as XML-based systems and web applications. Social analytics, CRM, financial, HR — there's plenty of data to go around.

Adding to the complexity, when organizations transition through M&As, whole new data resources come into play. Enterprises need technology in place to process and analyze continuously growing data.

Aggravating the issues that the sheer amount of data coming in causes, is an increased demand for fast information. Companies relying on spreadsheets to manage and deliver information quickly realize these systems can neither satisfy the first need — fast data analysis – nor the second — fast information delivery.

“Excel was created for accounting needs, not analysis," noted Jeremy Marsan. "As businesses began to rely on more data inputs from different parts of the company, they needed more robust tools to manage and manipulate data.” Today, this is true even for accounting. 

You Can’t Afford to Have Poor Quality Data

Poor quality data could be costing your company a lot of money. An infographic produced by Lemonly and Software AG reported that businesses can lose 10 to 25 percent of their revenue annually because of "bad data." 

Meanwhile, the U.S. economy forfeits well over $3 trillion every year due to bad data, and the healthcare industry loses $314 billion per year. Cleary it's a problem that quickly adds up.

While it would be inaccurate to attribute all of this loss to spreadsheets, solutions along the same lines are part of the equation. Outdated software, or software too small for the task, is part of the cause, but the root issue is likely reluctance to spend on better options. 

This is just bad math. Low quality data costs businesses much more than any nominal money saved by not investing in better management systems.

A Better Approach to Data 

So are spreadsheets useless? Of course not. For small-scale projects and individual organizational endeavors, they're still a great tool. And depending on their needs, small businesses might still get by with them in the short term. 

But medium to enterprise-sized organizations require timely and consistent access to comprehensive information they can size up in a single view.

An efficient information management strategy combines methods — both new and familiar — to address integral data issues such as integration, quality, metadata management and semantic reconciliation, and offers them as services.

However, before shopping for a new system, it’s important to remember no two organizations have exactly the same needs. This 7-step process is a good start to creating a custom framework that will provide:

  • A reliable data foundation
  • Agile access to real-time data
  • A single and consistent view of your enterprise

Whatever you decide, you'll benefit from more reliable data, delivered quickly, with cost savings over manual systems. 

Title image "IMG_0012" (CC BY 2.0) by  Bryce Edwards