We live in a search-based economy. We surround ourselves with increasingly complex information systems, from our intranet systems that hold vast amounts of corporate knowledge, to our social networks with hundreds of our connections and asynchronous conversations. Across all of that, we retrieve the information we need through search queries and search-based tools. As we look to the future, the problems we face are not about creating too much content and information, but in retrieving the information we need. The data we create is becoming more and more complex, and as a result, the front-end tools used to access the data are also becoming more complex. We need to reduce our information silos, yes, but we need to do it in a way that does not reduce functionality.
Most companies are constantly adding third-party and custom tools and reports to improve access and get more value out of our data. The almost constant reworking and shaping of data and systems came at a high cost in people, hardware, and time. Historically, the larger the data set, the slower the performance of our data queries (compute and processing time). Because of this, what tends to happen is that end users become frustrated with the performance and request specialized, focused solutions for their own team or project, creating yet another data silo focused on short-term needs. And the process repeats itself.
Limiting choice may sound counter-intuitive, but it can drive user behavior. Look no further than the restaurant industry. Some of the most successful fast food restaurants have very limited menu options. What they have discovered is that limiting the number of choices in their menus actually drives sales. Research into the topic at Columbia University has shown that when confronted with too many choices, customers struggle to make any decisions — and end up purchasing less. Additionally, a limited menu can mean a more streamlined and efficient kitchen, a much less complex supply chain for products and services (fewer suppliers might mean lower costs), and the ability to run operations with fewer personnel.
When optimizing database management, limiting your data set can improve performance and accuracy of results and reporting, because the limited scope allows you to refine and focus on specific data types and functions, and specialize the types of solutions you deliver. Rarely does a data analyst work against the complete database. Instead, they work on a slice of that data. A system or tool utilizing data that has been organized and optimized for specific queries, retrieving specific results, will perform better than a system that must query across multiple databases to find and present the relevant data set.
Even within the Office 365 platform, some teams have made the choice to limit the functionality made available to their organizations -- turning off features that they view as creating unnecessary information silos within the platform. The risk of this strategy is that the company may limit the collaborative needs of their end users. We should not limit the ability for our tools and systems to create data -- but we should be more thoughtful about how information is being captured, where it is captured, and how it should be retrieved.
Human nature is to solve the problems right in front of us. More difficult is to look at our problems more holistically — to step back and think about these issues long-term, and how else this data might be used. An operations team will look at solving their own needs, regardless of the potential benefits to their support or engineering teams. Likewise, support will develop solutions for support, and engineering for engineering. And finally, the IT team may limit functionality in an effort to make the system more manageable, or compliant with internal business requirements.
Architecting our systems holistically (and planning our businesses using systems-based thinking) can be difficult and time-consuming, but are necessary if we are to prepare ourselves for the unknowns.
We are siloed in our thinking about business problems, not just the data. It is understandable, since one team is not typically measured on the activities or optimization of other teams. From this perspective, not all data silo issues are bad. A smaller sub-set of data, or a spot-solution, allow us to act more quickly, developing responses that solve the problems at hand. But we can’t lose sight of the broader goals while chasing after short-term solutions. Ultimately, the organization loses value when people are not engaged within the system -- and employees become disengaged when they do not have the tools they need to be productive.
Much of the focus of company leadership is on solving the short-term problems: lowering capital expenditures, reducing operational costs, increasing revenue, and so forth, through cloud, social, and mobile strategies. But many of these decisions are made without fully understanding the long-term costs of these decisions.
At Beezy, one of the topics constantly being discussed is how we can give end users the functionality they need, while reducing the number of information siloes being managed. We recognize that we are at a major inflection point in the history of information technology, with pressures around decreasing costs and headcount, pushing data and functions to the cloud, to enable more social capabilities, and to build out mobility solutions. The danger is to fall into the data silo gap, and build out solutions that do not truly scale the enterprise, that do not look beyond solving the smaller problems before us without considering the long-term requirements of the business.
If you have not yet seen the award-winning Beezy solution, schedule a demo today and let us show you how our SharePoint and Office 365-based solution can help you reduce the information silos within your business, while giving your end users the functionality they need.