Challenges in Managing Data are Growing

Challenges in Managing Data are Growing

We believe there has never been a more important time for companies to focus on how they manage the ever growing and ever more complex data. They now have more information and are conducting more integration between systems than ever before. The data management challenges businesses now face are formidable:

• Mergers, acquisitions and globalization have brought about more rapidly changing technology environments. The technology adoption curve has now shifted from technology infrastructure and applications to information.

• Most large organizations are highly federated, with decentralized systems and processes resulting in data management problems that are extremely complex - both from a technology and governance perspective.

• There are large degrees of overlapping data among most organization’s systems. Data quality problems in one system may – or may not – be a problem in another. The distributed nature of this problem from an organizational perspective presents issues for traditional project delivery models.

• Most organizations have spent the past decade removing their manual processes and automating the integration of their systems. Removing these controls can actually increase the risk of propagating poor information and can result in a greater chance of system failures without a well-defined architecture.

• The biggest challenge with large-scale and complex technology change is the data. There is no choice but to fix the issues of the past – you can’t “start over”.

Looking at Data Governance

We’ve all known it for many years and history has demonstrated over and over again:
data is the force behind any successful business. How an organization uses its data can be the difference between average performance and competitive advantage. For this reason, it is vital to have a data management strategy that focuses on the creation of accurate, consistent and transparent data content that can be integrated into the business applications and business processes.

Over the past weeks, we have been asking the following questions of a number of CIO’s and CFO’s at large local businesses: who “owns” the data within your enterprise? Who makes sure it’s accurate? Who makes sure it’s available for use at any time?

The answers weren’t all that surprising. Most often people nobody really “owns” most of the data. The CFO’s appeared to want to “own” the financial data – that which is represented in their formal filings. Data ownership in other parts of the business, like production, manufacturing, distribution, marketing, seems to flounder somewhat. But the one thing we heard most often – “data ownership is NOT the responsibility of the CIO”.

So if data is the force behind successful businesses, wouldn't it be important to have the owners of the data know they own it and give them the tools to make sure they are successful? We think having Data Governance is an important step in managing data. But that Data Governance is only one piece of a much larger program required to properly manage enterprise data. And how do you create an enterprise data management program?

We think it starts by looking at enterprise data in a holistic manner. Have a data strategy. Work through the data governance models. Look at all the different types of data and how it is used and why it's so important to your organization.

We have built a comprehensive Enterprise Data Management framework that we use this to look at and evaluate where a company is with their environment and how they can use process, people, and technology to address data. More on that over the next few posts.

Answering the Challenge

Corporations, government bodies, and not-for-profits have each recognized the value of enterprise-wide software solutions – with more of them running SAP than any other ERP. Those that have undergone the implementation process have already encountered the daunting challenge: getting data from numerous disparate systems into a single cohesive data repository which the enterprise-wide resource planning system can draw upon. The unanswered challenge is controlling the risk of migrating legacy system data with the absolute confidence that it will work properly in the new system. The question often facing CxO’s is how to make it a predictable success. The question is how to make the legacy data of good quality enough data that it will run correctly in the new ERP environment.

Change occurs slowly in every industry, but certain major events act as a catalyst that cause people to address issues that have long been in sight. Considering the economic environment of today, corporations are reviewing all of their processes – including how they manage the risk associated with their enterprise data. If a company has historical data in a legacy system, it can become distorted through time. Gartner Research indicates that data degrades at the rate of about 2% per month. That implies at the end of just one year, the system may have approximately a quarter of their data invalid. This is what has become the “standard” in the industry. This is what historically has been acceptable. We believe there is an obvious need to control the risk. This risk spans the entire life cycle of data. This risk reaches into reports and decisions based upon that bad data. Executive management at most companies are counting on their systems to reflect the reality of the business.

Black Watch Data Meets the Unanswered Challenge…

Our management team has extensive experience of hundreds of successful implementations, been responsible for consulting teams, been executive sponsors, and been responsible for business transformations. This team has developed a new way to meet the unanswered challenge. We created our solutions based on an integration of a number of tools from SAP BusinessObjects, SAP’s MDM and our own proprietary software combined with an implementation methodology that controls the risk of data for the entire data life cycle.

Finally the market has the full resources to manage the unanswered risk of the Data Life Cycle. Black Watch is on a mission to provide Zero Defect Data™.

The Beginning

Welcome to Black Watch Data.

Companies that have already migrated to an enterprise ERP system are familiar with the central challenge in such an implementation; migrating data from many disparate systems into a single integrated system that, as the central repository, must continue to feed or draw data from multiple linked systems. Because data management isn’t a onetime task, the question remains how to make it a predictable success. ASUG’s recent survey stated that “93% of companies experience significant data issues during their most recent implementation" and seems to suggest that no one has come up with a good answer.

Until now that is.

Until Black Watch.

The path to a successful data migration is narrow, the choices of dealing with the many difficult complications are very few. Some companies confront this challenge by adding additional people to the data cleansing activities in hopes that more eyes and hands will increase the odds of having correct data. Rather than shutting a business down at 'go-live', some companies go ahead and 'go-live' with questionable data. In worse case scenarios, companies revert back to the legacy system after their 'go-live'.

It doesn’t have to be that scary.

Black Watch has a better way.

Our way is with Zero Defect Data. We have created a comprehensive solution to minimize the risk of a project: Data Teams that have extensive SAP experience utilizing cutting edge technologies and proven methodologies.

Welcome to Black Watch Data.