The rewards for using data are big. Smart organizations are using it to improve user experience, personalize interactions, improve loyalty and usage, create better products and processes, improve quality, lower waste, leverage preventive maintenance and reduce costs. In other words, data is the perfect ingredient to put a smile on the faces of customers, employees and stakeholders. And yet, according to Forrester Research, less than 10% of enterprises generate advanced insights driven by data. Something is going wrong.
It isn’t easy going for Chief Data Officers (CDO) and Chief Analytics Officers (CAO). The tools and technologies around data (image recognition, automation, artificial intelligence, stream analytics, machine learning, data visualization, etc.) are not just difficult to harness, but in the wrong hands, they often throw up frustratingly irrational results.
In addition, there are the challenges of trying to figure out where to apply data sciences. Should it be to projects that improve customer experience, that create new learning or improve existing processes? Should it be to projects that add to revenue, improve market share or reduce costs? Prioritizing the goals of data analytics can become confusing. Without adequate guidance, enterprise can quickly go down the wrong path with investments, time and resources.
Finally, once you’ve mastered the technology and clarified the business goals, there remains the business of actual data collection. Organizations have been collecting data for ages. Now they have even more options, ranging from their own data stores and customer interactions to data hunters, brokers, aggregators, public databases, syndication services and very sophisticated data ecosystems. The data supply side is exploding. It is a problem of plenty.
To further complicate matters, this is a fast changing area of technology, forcing most organizations to acquire the types of data that their existing tools and skill sets can manage. Senior executives will readily acknowledge that this is a problem. They must still rely on gut feel and personal judgment. This is not altogether bad. If anything, an experienced and confident executive who is driven by instinct is an asset. It is even better when the executive is right most of the time. But the fact remains that this kind of business instinct needs to be institutionalized if it is to scale across the organization and if it is to survive the executive--which brings us back to the problem of data collection, acquisition and quantifying its benefits.
This leads us to the four key issues that enterprises must keep in mind when dealing with data to generate business insights:
- Identifying the right projects that benefit from data
- Sourcing the right data (type, volume, quality)
- Quantifying the benefits of using data
- Putting the right resources behind #1 and #2
These appear to be simple goals. However, CDOs and CAOs will readily agree that this is not the case. With very little time to ramp up data and analytical capabilities within the enterprise before competition gets there, CDOs and CAOs would do well to team up with reliable data consultants. It’s the painless—and effective—path to building a strong data driven organization.
Check out this webinar to understand how your organizations can take confident and sure steps to a data-driven future.