If you haven’t yet made reservations for tonight, bought flowers or chocolates, or a decadent gift, you *may* still have time. Or you may not. Today, of course, is Valentine’s Day. The day unofficially set aside to shower our romantic partners with tokens of love and appreciation – and Americans tend to celebrate with gusto. According to the National Retail Foundation, we will spend more than $20B this year, making it second only to Christmas in total amount spent on a holiday annually.

In the same survey, however, while total spending is expected to be up over last year (and some 20% of that spending dedicated to pets), NRF expects only 51% of Americans to even celebrate Valentine’s Day. The study doesn’t probe into the reasons that a near majority of Americans don’t plan to make any Valentine’s Day purchases, but they are dedicated to research into retail trends while that investigation might best be carried out by a therapist. For many who are single or in a failing relationship, the day can present feelings of anxiety and depression that can’t be cured by chocolate-covered strawberries.

Do You “Choo-Choo-Choose” Your Enterprise Data?

What is your relationship with your most valuable corporate asset – your data? If you could, would you be sending it flowers and chocolates? Or would you more likely be inclined to contact a qualified counselor to offer couples or one-on-one therapy? If it’s the latter, you aren’t alone.

A newly published survey from the Harvard Business Review reports that:

  • 72% of survey participants report that they have yet to forge a data culture
  • 69% report that they have not created a data-driven organization
  • 53% state that they are not yet treating data as a business asset
  • 52% admit that they are not competing on data and analytics

These statistics are sobering, especially in light of these:

  • Gartner Research revealed a survey last year that stated: “organizations believe poor data quality to be responsible for an average of $15 million per year in losses.”
  • IBM goes a little further and estimates that the yearly cost of poor quality data, in the US alone, in 2016, was closer to $3.1 Trillion.

Improve Your Relationship With Data Intelligence

Everyone wants their organization to be data-driven. The goal of making all decisions based on accurate, up-to-date information is driving the core of digital transformation efforts, and for that to happen your data needs to be actionable. And, for your data to be actionable, it needs to be part of an intelligent lifecycle that includes:

  • Data Acquisition & Quality – Data exists in silos. It is divided along departmental and geographical lines. It lives in business applications, legacy systems, and, yes, much too often, spreadsheets. The owners of the data protect it passionately, but, only care about the aspects of the whole picture of a Customer, Product, Location, Account, etc, that they care about – and they standardize the data they care about in the way that is most beneficial to their end goals. A Data Intelligence architecture must first break down those silos and integrate all enterprise information into a single location in which ETL, standardization, deduplication, and stewardship processes can be applied to the data to improve quality and make it ready for use across the enterprise.
  • Master Data Management – At its most basic element, master data is the core set of data elements and attributes that describe the key entities at the heart of an enterprise. A typical organization may rely on data domains like Customer, Product, Asset, Location, Supplier, Part, Account, or more to feed business applications and to make decisions. Mastering that data in an MDM hub that includes business process management, workflows, collaboration, stewardship capabilities, enrichment, relationship modeling, syndication, and multi-channel publication contributes to the overall intelligence of an enterprise architecture.
  • Data Governance – Accurate, up-to-date data needs to be accessible to any user within the corporation who needs access. In addition to ensuring that access rights are applied correctly and upheld, processes should be in place to monitor and approve any changes to key data so that all users receive the same data when making an authorized request. Data Governance processes and tools, like catalogs and approval workflows, are integral to maintain the health and democratization of your most important asset.
  • Business Intelligence & Analytics – An intelligent data platform requires constant monitoring, reporting, and improvement. Business Intelligence is more than just creating the next AI feature for your customers (although that can be very important). It’s also about viewing real-time, historical and predictive reports on trends within your organization, your market, and your customer base. Just as the old adage “garbage in, garbage out” was true in the days when Enterprise Data Warehousing was the most popular trend in data management, it is equally applicable to a new paradigm of Big Data and data lakes.

Unfortunately, as with most things, there is no single “silver bullet” to make your enterprise data “intelligent.” Implementing a Data Intelligence architecture requires multiple technologies, each fitted to your organization’s unique business requirements, Change Management, and most importantly, a careful and well thought out strategy and roadmap for success. At Amplifi, we believe in the power of intelligent data, and our team of consultants and technology partners can help you love your enterprise data again.  Maybe next Valentine’s Day you will send it flowers. Contact us today to find out how we can get you there.