There are many ways to put data to work. Companies, especially their leaders, are advised to explore as many options as they can. While big data, analytics, artificial intelligence, and the Internet of Things garner the lion’s share of media attention, using data to its full potential is much more about management than it is about technology. Putting data to work includes the whole sequence - from data to insight to profit.  Maintaining a proper data backup and recovery solution is key to building trust and saving costs with your company's data as well.  As Managed IT Services providers, we deal in data all the time.

Analytics are Critical to a Company's Performance

In working with companies on getting more from their data, I advise managers to explore seven methods for putting data to work. I also urge all leaders to initiate department or business unit-size trials of all these methods, so that they can learn how the options work and which would be best for their business.  Thomas Redman provides the following examples of how your company can manage its data:

  • Make better decisions. First, use better (more relevant, more accurate) data when making decisions, up and down the organization chart. I’ve not worked with or heard of a company that didn’t freely admit that it needed to make better decisions — and many push hard to improve. But incorporating more and better data into decision-making can be difficult. You must learn to understand variation, to combine data from different sources, and to drive decision making to the lowest possible level. By taking the time to learn these skills, though, you can use data to reduce uncertainty, increasing the chances of making sound decisions.
  • Innovate products, services, and processes. Use data to uncover hidden insights, and use those insights to create or improve products, services, and processes. For example, at Morgan Stanley, Jeff McMillan and his team aim to improve working relationships with their wealth management clients by analyzing everything from client goals and portfolios to available investment products to email. An algorithm then takes this information and suggests actions, at which point advisors choose the best ones to suggest to their clients.  Their goal is to develop personalized strategies for each client based on far more data and analytic horsepower than any financial adviser could marshal alone.
  • Informationalize products, services and processes. Build more data into what you offer customers, so you make existing products more valuable. Automobile manufacturers have a history of working on this by adding warning lights, GPS, distance-to-empty gas tank notifications, and other features almost seamlessly. I’ve yet to run across a product or process that wouldn’t benefit from more data.
  • Improve quality, eliminate costs, and build trust. Proactively address quality by finding and eliminating the root causes of errors. Virtually everything a company does, from delivering products to running the place, uses enormous quantities of data. But bad data makes this work more difficult and increases costs — up to 20% of revenue! You can’t expect someone to factor data they don’t trust into an important decision. Take steps to actively track down data quality issues and eliminate their root causes.  Including a Data Backup and Recovery plan for your companies data is key to eliminating expenses and data loss that can result in hundreds of thousands of dollars lost, and build trust.
  • Provide content. Sell or license new, richer, or more targeted data. All customers depend on content, and thousands of companies, such as Bloomberg and 23andMe, aim to fill the need. Still, most companies don’t think much about selling their data. But doing so can provide great opportunity. For example, car insurance companies discovered a relatively simple piece of data they could sell: the number of new policies written each day. New car sales reflect the health of automobile manufacturers and are of great interest to investors, but manufacturers release sales figures monthly — an eternity for investors. Since each sale requires a new insurance policy, the number of new policies issued each day provides a faster indicator. This becomes a profit stream for the issuers and for Quandl, which aggregates this data across the industry and packages it for investors.
  • Infomediate. Connect data providers and those who need the data. Here, the goal is not to provide content but to provide direction toward content. Google is, of course, the best-known example, but Quora, too, helps people find answers when expert help is needed. And there is huge opportunity here for others. In both their personal and professional lives, individuals spend hours each week looking for documents, reports, and other data. Find ways to connect these individuals with others who can provide the answers they’re looking for.
  • Exploit asymmetries. An asymmetry arises when one side of a transaction knows something that the other doesn’t. Exploiting this knowledge helps them drive a better deal. Hedge funds and used car dealers use such data to create and leverage asymmetries. More recently, sports venues, airlines, and others have begun using variable pricing to capture maximum revenue from consumers. All companies can examine sales and related data more deeply in search of such opportunities. Conversely, closing asymmetries, as Carfax does for used cars, can also present great opportunities.

Natural Networks is a managed IT services provider and we work with data on a day-to-day basis.  Knowing the best ways to manage and store your data is key to maintaining a good working environment for you and your employees.  If you want to learn more about our managed IT services and how we can help you manage your data better, contact us today!