Don’t be a victim of your own success
When a company spots a lucrative gap in the market or comes up with an innovative new business model, it can trigger sudden, exponential growth. However, many growing enterprises fail to sustain their initial surge in momentum—or may even collapse dramatically.
One of the things that can put the brakes on company growth is a failure to scale up the processes and infrastructure around big data and analytics. As data science becomes an increasingly important source of competitive advantage, it’s an issue that companies can’t afford to ignore.
In a small startup, sharing and keeping track of data assets may not be a big deal. But as soon as you have more than a handful of employees, data challenges will become apparent. A host of difficult questions suddenly need to be answered, such as “Where is my data stored? Who is authorized to access it, and how are they permitted to use it? Is my organization using data to its full potential, or are my knowledge workers and data stewards tied up with time-consuming tasks like data discovery and preparation?”
At the same time, data volumes tend to rise dramatically as the business grows, while business users need insights faster than ever before to outsmart smaller, more agile rivals. The accelerating pace of decision-making means that companies can no longer afford institutional bottlenecks—such as a central IT team acting as gatekeeper for the company’s data—that slow down essential analytics processes.
Some organizations have already broken free by providing self-service analytics to employees. However, in doing so, they need to find a new approach to governance. Data access cannot be a free-for-all, but it also can’t wait for every request for access to be approved manually by the data stewards. A self-service approach also exacerbates the complexity of data findability and increases the likelihood of redundant data wrangling and analysis.
As we discussed in a previous blog “The million-dollar question: where is my data?”, more companies are recruiting chief data officers (CDOs) in an attempt to mitigate these challenges. But CDOs cannot work miracles on their own; they need the right technology to help them succeed in their mission.
Standing on the shoulders of giants
Companies across almost every industry are opening up and becoming more transparent. Rather than each line of business jealously guarding the secrets of its own success, they are recognizing that taking a more collaborative approach and breaking down silos within their organization is the best way forward. Take the example of newspapers moving from a daily edition to a 24/7 rolling news model. They no longer have a single chief editor checking every word; that isn’t physically possible with today’s news cycles. Instead, the responsibility for checking and editing is shared more widely within the organization, and each employee has more accountability for their own contributions.
Similarly, with the right tools, like intelligent data cataloging, organizations can empower their employees to become data stewards and help curate and govern data via a more decentralized, bottom-up model. Often, the best judges of data assets are those who create or own them and those who use them. To support the central team of data stewards and custodians in your CDO’s office, why not take advantage of the expertise of your knowledge workers and have them take some of the responsibility for data stewardship themselves?
The Role Data Stewards Play
Even if these users don’t fully understand all the intricacies of your data governance policies, they can still play a valuable role in classifying an asset—especially when combined with a metadata discovery tool that automatically applies relevant rules based on the classifications they select. A solution such as IBM Data Catalog (currently in closed beta) can provide these capabilities, meaning that the CDO’s team can focus on setting the right governance rules and policies rather than reviewing and managing access to individual data assets.
For a corporation with international operations that may need to navigate data sovereignty rules that differ from country to country, these capabilities can be especially useful. They can help companies seize control of varied data governance policies while enabling access to assets, which can be transformative.
Trust and enable your teams
Don’t lose all the hard work your employees have applied toward data in the past. Give your workforce the ability to tag and comment on the provenance, quality and usage of data assets, and you can dramatically improve the results of future analytics.
Although the issues we’ve discussed intensify with increasing company size, they start to emerge very early in an enterprise’s growth. Any organization that generates or uses a lot of data can benefit from the capabilities we have described. By demonstrating trust in your employees, you can utilize the power of your network to enable more effective use of data and reap true competitive advantage.