How Data Silos are hurting your business
It’s all about the DATA in Publishing
There’s a saying in the publishing industry that “Content is King”, meaning that the creation and curation of the written word is of paramount importance. And it’s still mostly true, but recently we are seeing a new challenger to the throne. Many publishers are heavily invested in technology and have developed significant revenues from webinars, events, and social media outreach. The new “king” in all this is DATA, “Big Data” as it’s often called, and unfortunately along with all that big data comes a potentially big problem.
It’s true that the availability of business data in publishing is significant compared to other industries. Publishers collect data from many sources: from prospects and customers, from their own internal systems, from social media, the internet, and even competitors. There’s no shortage of good data for publishers – the problem is that it’s not organized or collated into information that allows business leaders to make thoughtful business decisions.
The Silo Problem
Because of the variety of sources, the data that publishers collect results in data silos, or banks of separate data, gathered mainly for consumption by legacy applications. This makes it difficult for management to visualize the “big picture” without the right tools – and, perhaps more importantly, the right culture.
There are several things that publishers can do to transform this siloed data into valuable information. And to solve the question, we need to look at the root causes of the silo issue. They are threefold:
- Organization structure
- Company culture, and
- Outdated legacy software
Publishing companies, like in other industries, are often organized around business functions such as marketing, sales, and production. And the data that each department needs to address their own requirements is often function specific, rather than an outward-looking business orientation. We must consider data more as a company-wide resource that is department-agnostic, rather than viewing it as responding solely to a particular department’s needs. No single department should “own” the data; ideally, it should be viewed as a shared asset.
The problem above is often exacerbated because many departments don’t work together, although they do share select aspects of the same data, and this can result in some departments denying access to data that they regard as their own, based on the application in question. And with the abundance of cloud applications available today, it’s not uncommon to have a “Shadow IT” problem, where systems are operated in individual departments that are invisible to the company’s central IT organization.
Legacy systems that were designed to address the needs of specific functional applications tend to isolate data into silos anyway. These silos are difficult to integrate into newer external systems and often are poorly supported because the skilled resources are no longer available. Loosely related legacy systems often accumulate in organizations that have no standard approach to technology and do not employ a single technology platform.
The net result is that publishers often have a lack of coordinated, unified data, where duplication abounds (often leading to turf wars and infighting over whose data is better), resulting in higher costs, poor productivity and limited collaboration. No wonder management is frustrated with their inability to see the big picture!
Like many business challenges, this issue cannot be resolved without the active support of top leadership. Re-thinking of data as a company resource takes dedication and commitment from the top of the organization to change company culture, and where necessary, the organization AND the product. Leadership must commit to a single open platform in which data is seen from a customer’s viewpoint. To be more successful, leaders must change the company culture from one which is product-centric, to one which is customer-centric. The effort must be focused and sustained – not a temporary effort. It demands an ongoing process of continuous development based on field data. A good example of this is that of a well-known on-line financial newsfeed that adapts its subscriber content using real-time data based on the viewer’s geographic location at the time the copy is being delivered. They actually shrink the feed to supply only geographically-relevant information that is much more likely to generate immediate interest and create a loyal long-term customer. The information is valuable to the reader because it’s precise, timely and tailored to that particular reader’s interest on an ongoing basis.
How is this done in practice?
It’s important to look at customer sales, not as single transactions, but as a customer journey, by building a community with buyers. Modern software can help. Customer Engagement and Audience Building software are important to the mission of creating customer loyalty. The software develops a “persona” which defines the characteristics and behavior of the ideal target customer. Then by matching the massive files of acquired consumer data to the “persona” using AI and machine learning, the publisher can then create targeted marketing and social media campaigns addressed directly to those matched individuals. The publisher distributes timely promotional content that matches that customer’s behavior and perspectives and is more likely to develop and maintain a long-term customer relationship with the recipient.
Of course, before the “massive files” of consumer data can be used in this way, we need to unify the data, so that it is “de-siloed”, matched and merged and duplicate data eliminated. It demands a centralized information processing model, where functions are integrated. It contains pre-built interfaces to external systems such as Salesforce and Oracle at the front-end, and Business Intelligence at the back end that allow users to begin to identify commonality and patterns in the information. The use of real-time dashboards, for example, helps in presenting condensed and coordinated views of customer behavior, and as a result, provides real insights into how, when, and through which media one should best address that particular prospect.
The essential first step is to change the company culture to treat data as an application-agnostic, company-wide resource, gathered from many internal and external sources, that is managed and controlled centrally on a single platform.
If we do that, we may yet realize the holy grail of providing management with real and timely insights into how to get and keep a customer.
CEO, knk Software LP