The common discourse on analytics says they are a huge asset. But they are also too complicated and too expensive for enterprises to handle in-house. That has motivated many companies to outsource their business analytics capabilities. And more than a few are underwhelmed by the outcomes.
Business Analytics Challenges
It’s true that outsourced analytics seem like an asset at first. They allow companies eager to dive into data to rely on ready-made tools and outside expertise. But over time those exact advantages prove to be limitations.
Since the tools are ready-made they lack the flexibility to adapt to user needs and change with the company’s evolving demands. And since so much of the responsibility is handed over to outsiders, companies lose the ability to work with data on their own terms.
At first this manifests itself as a limitation. But it quickly evolves into a liability. Companies can’t make the most of data that contains significant strategic insights. And they can’t feel confident the insights they are getting are complete and accurate. Worst of all, byzantine data networks constructed according to the requirements of the analytics provider take forever to produce reports and generate actionable intelligence.
Companies understand that advanced analytics is an asset that is quickly becoming essential. And that is why there is a serious push to bring analytics in-house. Thanks to advances in technology and innovations in data science, the confusing and costly solutions of the past are more accessible than ever.
It does not take a major capital investment in hardware and licensing fees to get the necessary technical capabilities; It does not require an army of data scientists to get the necessary technical expertise; And it does not require an intense effort to make the most of the data on hand.
In-house analytics is a very real possibility, and in practice the benefits are significant:
- Rely on Intuitive Discovery Tools – In-house analytics remove the intermediary between end users and data. Simple tools like relational search allow users to explore huge data sets using commands and interfaces they’re already familiar with. Decision makers at all levels do not have to request data and then wait patiently. Instead, they conduct the search on their own.
- Create Custom Standards for Governance – In-house analytics allow enterprises to establish their own company-wide standards for governance. And when everyone is operating according to the same rules it improves the opportunity for discovery while alleviating certain security concerns.
- Facilitate Lightning-Fast Performance – In-house analytics streamline the underlying data architecture to speed up performance significantly. In the best cases the time to insight is 1,000 times faster. Despite the gains in speed, this in-house tech has the advanced analytics capabilities to generate more meaningful insights.
- Scale Without Concern to Limits – In-house analytics tools currently available scale much faster and more flexibly than many of the second-generation business intelligence tools favored by providers. Users are able to engage with billions of rows of data without concern that crucial facts and figures have been excluded from the data sets.
- Combine Data from Multiple Sources – In-house analytics offers greater flexibility in terms of what data sources are integrated. Companies are not bound by the limits of a provider. Instead, they are able to draw deep comparisons and perform sophisticated analysis that encompasses every relevant insight.
Outsourced business analytics is not a bad option, it’s just not the best option. And now that the analytics has become so central to business outcomes it’s not sustainable to rely on a second-rate solution. By bringing analytics within your organization you are in the driver seat of your own success.