As CIOs increase their strategic contribution, mobility provides a key entry point. Start with five critical moves.
The bottom line
What: Use mobile data to provide unprecedented business insight.
Why: As IT moves from “cost center” to strategic partner, CIOs have to up their game.
How: IT ingests more business-relevant data than ever before. Time to use it.
IT has access to information the business never had before—plus the tools and skills to better interpret that data than ever before. Not just about the infrastructure and applications that IT provides, but about how end users actually interact with the enterprise. That information gives IT leaders a great opportunity to be better strategic partners to the business.
While there are many sources of potential insight, the most interesting avenue right now may be mobile technology. A mobile app can be the gateway to insights that improve development, design, sales and marketing—even influence new product offerings, says Lorna Hardie, HP Software Country Manager South Africa.
“When someone has a mobile device in hand,” Hardie says, “it’s not just about the browser and app. The device itself generates a lot of micro-behavioural information that is very valuable, if you can put it to use—hesitation, clicks, the time it takes to make a choice, and so on. That telemetry is not just diagnostic; it’s valuable design and marketing information.”
So the information is there, as is the pressure on IT to provide innovative value. Where do you start?
“Find a sponsor on the business side to let you apply analytics to something that the business really cares about,” recommends Stephen Smith Pre-Sales lead for HP Software South Africa. “You want to avoid the ‘it’s too expensive until you can prove all the results’ attitude.”
Embracing data science and analytics
CIOs need a plan to bring new insight to the business—from every data source, not just mobile. How you do that depends, of course, on your type of business and IT organization, but here are five starting points:
1. Know what you know. Examine the data stream coming from your mobile devices, both software-generated and device-generated (or whatever source provides the best starting point for your organization). Work with your business units to decide which data is most valuable and what actions might be taken in response to smart analysis.
2. Hire (or rent) a data scientist. Consider the value of adding at least one expert analyst to your team. Traditionally, that has meant a data scientist with strong expertise in examining correlations and statistical patterns, but this is gradually changing as analytics tools advance and become more visual and easier to understand.
3. Start small and prove value quickly. For some businesses, it makes sense to launch a trial project—so that you can immediately prove the value of analytics to the business, then move to bigger things. Smith advises starting with what other organizations have done: “Your best approach may be to say, ‘We’ll analyze unstructured data that has been proven useful elsewhere, and prove it here for a quick win.'”
4. Ingest and analyze. Deploy a sophisticated data collection/ingestion engine. Ingest data and drop it into a powerful database that facilitates real-time access and retrieval. Then apply advanced analytics (context-aware, intelligent, and able to facilitate quick decision-making).
In the era of Big Data, there’s no shortage of choices in both data collection platforms and analytics software. The trick is to choose very carefully according to your information needs. In the experimental stage, you might succeed with limited trial software or cloud-based services.
5. Deliver insights to the business. Connect data with the developers and marketers who can get things in front of customers quickly, taking advantage of business opportunities as fast as they arise.
Letting the data prove what’s best for the business
Beyond quick wins, you need a longer-term strategy—but not one set in stone. IT and business both need to become more experimental in order to thrive in an increasingly competitive marketplace. That ultimately means—through intelligent trial and well-managed error—letting the data prove what’s best.
And the faster you can do this, the better.