“In information technology, legacy applications and data are those that have been inherited from languages, platforms, and techniques earlier than current technology. Most enterprises who use computers have legacy applications and databases that serve critical business needs.” SearchDataCenter.com

It used to be that when we referred to applications that an organization had invested in over time, and nurtured through the years, that we avoided the term “legacy”. There was a fear the word could convey negative overtones, be construed as a disparaging term for something old and locked in the past.

But if this negative perception was ever true, it certainly isn’t today. In our current economic climate of thriftiness the concept of re-use and extending the life of existing applications has become increasingly attractive. Businesses are looking to make the most of the investment in these often bespoke applications, and to get even greater return on their spend.

Exciting new tools and technologies that integrate with these legacy applications can provide a “best of both worlds” solution. The existing applications that often provide the crucial competitive advantage for an organization can be utilized to the max with the latest initiatives, to provide cutting edge and inexpensive solutions that keep a business agile.

Legacy data and applications have unashamedly become something to be proud of. They have a part to play in the ongoing success of organizations fighting to stay ahead of their competitors.

The term “legacy”, it turns out, is actually very appropriate in a positive way… something valuable is being handed down from the past to continue to enhance the future of the organization. 

One of the greatest things about the letter ‘V’ is that turned to either side, it either means greater than or less than. This might be why ‘The 3 V’s’ (volume, variety and velocity) have become so important when discussing Big Data – because managing your data can truly determine whether or not your company is greater or less than the competition.

Let’s start with what big data is; a white paper by McKinsey Global Institute calls big data, “datasets whose size is beyond the ability of typical database software tools to capture, store, manage and analyze.” We chose this definition (there are many) because it illustrates that there is no true size of “big data”. The one thing that’s certain is that corporate data is growing at a rapid clip. The report above estimates that global data is growing at more than 40% per year. 

If you’re not getting ahead of the game and coming up with a plan to manage your data, you’re missing out on a huge revenue opportunity. Would your company change the way they did business if they could see all of the data available – volume? How could your company grow if it had the ability to see into buyer trends, demographics and product performance - variety?  How quickly would you grow if you were able to make quick - or even automated decisions – velocity?

Decision making is best done with a holistic view of what’s happening today. A major problem that nearly every organization faces is that today’s data, if gathered, generally becomes a closely guarded secret within various departments and therefore decisions are then made departmentally – and become departmentally dependant, which doesn’t allow for management to measure performance across the entire organization.

Fear not, there is help and you can read more about that here, but keep one thing in mind, exposure helps with accountability and ultimately, an efficient increase in revenue opportunity.

I keep 15 years worth of tax returns. My accountant told me that I don’t need to keep any more than 5 years, but I’m always fearful of an audit. Of course, these documents are in paper form, in an unmarked box in the attic, or possibly in the basement – where storage is at a premium. I know that they’re there, but it certainly wouldn’t be easy or convenient to locate them in the event they were needed.

Of course, then there’s always the risk of a house fire or some other disaster that could make my years of hoarding all for nothing.

This is often what happens to data in our legacy environments. As applications evolve and we get used to having easy, immediate access to necessary data, it becomes increasingly challenging to go back to old systems to retrieve data. Even if easily found, the data output is often hard to manipulate and retrieve in a useable format. If you only rarely access this data, then the occasional time consuming retrieval and cleansing may be fine. But if you need to look at data in your legacy systems frequently, this can be a real productivity issue.

In addition to the loss of productivity, there could be a financial impact if you’re maintaining old systems with hefty costs. It’s necessary to consider whether the benefit of retiring old systems and applications outweighs the associated risk. In addition, companies should carefully consider the best way to ensure that legacy data is moved from a legacy environment to a more current architecture.

To learn more about our methodology, and how we can help your organization determine the best plan for the future for your legacy systems, take a look at our White Paper on Process Oriented Planning.

Extract, Transform, Load – or ETL – software packages have taken the market by storm in the last 5 years. Like the majority of today’s software, someone, somewhere, was banging their head against a brick wall day in and day out and developed a permanent way to fix it.  Released to a larger audience, with source code, geeks everywhere went out to make their mark in the development community and added and enhanced these free tools. But, we all know that nothing is truly free. Especially if one or more of your data sources is located in a legacy environment.

So, how do you decide if your company should make a financial investment in a Master Data Management (MDM) tool? Here are few points to consider:

·         Do you have data in legacy environments?

·         Do you have a very large amount of data that you need to cleanse?

·         Do you need the process to be repeatable?

·         Is the data that you’re manipulating critical to your organization?

If you answered “yes” to any of the above questions, you should consider thinking about the old adage, “you get what you pay for”. Free ETL software is not usually flexible enough to handle complex ETL needs, and if you’re trying to access data in non-relational environments, it’s almost assuredly not going to be able to help – at least not without a fee.

But, probably the most important item to consider is the value of your data. Is this data that will be used by sales and marketing to drive the revenue of your organization? Does this data house critical financial information? Would your company be significantly impacted if this data was lost? Are decisions being made about business with incomplete data?

Over the last several years, the already acronym saturated IT industry was introduced to a new set of letters aimed at improving profits to organizations. Sales Force Automation (SFA) and Customer Relationship Management (CRM) began to infiltrate most Enterprise companies. These systems were designed to increase the throughput of information and streamline the sales and marketing organization while allowing “The Man in the corner office” full insight into the company’s performance and operational efficiency.

While this certainly gives us more squares on the buzzword bingo card, over the years it’s proven that these tools do increase a company’s visibility into performance and improves future forecasting. Unfortunately, often times all of the data that is needed for this holistic view is housed in several different IT systems. This can create a headache for an already over-worked, under resourced and underappreciated IT department.

If all of this wasn’t enough, it often seems like every person in the company wants these numbers in a different format at different intervals. What does all of this mean? More acronyms and an entire industry focused Business Process Management (BPM), Enterprise Performance Management (EPM) and Business Intelligence (BI) – a more than $10B industry according to Gartner.

But most organizations still depend on data from multiple sources. DestinationCRM.com states that a recent Aberdeen report shows data integrity as a key “hidden cost” in business intelligence. The report goes on to state that best in class companies are twice as likely to invest in tools that integrate and cleanse disparate data sources. Given the recent constraints to IT departments, instituting a data management tool up front can save time spent manually gathering data to meet business intelligence requirements. According to the report, company projects can reduce the time to complete by nearly a third when given better BI tools.

As executives, sales and even finance departments look to automate faster access to more data, it makes sense for IT teams to find ways to automate the delivery of this data to end users. And while there’s a multitude of open source software able to address the data cleansing challenge, few (if any) can truly give record level access or automate the cleansing process once it’s established. This is why investing in a data cleansing tool can be quite a cost saving long term.

While most of the acronyms I mentioned in this blog have been known in the management community, my next blog will focus on the 3 letters that are important to your IT/Data team – Extract, Transform, Load or ETL.