In one case, Georgia-Pacific wanted to take a more advanced approach to handle its data and used Amazon Web Services (AWS) to help.
The company knew that downtime with some of its machinery could cost the company millions of dollars per year.
It used data analytics to help predict some equipment failures up to three months in advance.
Spend time thinking about existing pain points in your company that big data could address.
Then, reserve some time during your pitch to highlight why analytics could provide such promising possibilities.
Your boss may fear that increasing the companys investment could enable data scientists to extract more insights while leaving others in the dark.
However, some companies use analytics in ways that break down the barriers that information might otherwise pose.
In one example of a data science success story, TD Bank wanted to make it easier for analysts to utilize the companys information without requiring too much help from data scientists.
It ultimately made data sets more available for everyone who needed them to use.
TD Bank also devoted time to assessing which tools would help it achieve that goal.
If your boss feels that analytics would make the companys information solely accessible to data experts, be proactive to ease that worry.
You could suggest that your boss create a list of the must-have features of a data analysis tool, then offer to spend time researching which software has those offerings.
In addition to bringing up companies that are using data analytics and getting satisfying results, try to include statistics in the pitch to your boss.
Its ideal if you can find information related to things like money saved, improved productivity or better customer interactions.
Its more impactful if you can mention that a company from your industry saw a 72% cost savings benefit one year after allocating more of its budget to data science instead of saying it saw a substantial increase.
Be as specific as possible as you describe the benefits your boss is likely to see after incorporating data science.
One of the primary advantages of data analytics software is that it can extract results from huge amounts of information in much less time than humans can.
You can keep that in mind while discussing how failing to bring data science into the business could mean the company is not adequately informed.
For example, data analytics could show that millennials arent responding well to a particular marketing campaign, but people from 40-50 like it the most.
It may indicate that a certain city is an excellent location for a new branch based on the number of calls from customers who want it there.
Angle your pitch to make it clear that data analytics investments are increasingly necessary in this day in age.
They keep people more informed than theyd likely be without such technology.
Besides keeping these tips in mind, remember that it may take more than one serious conversation with your boss to convince them to give the nod of approval to data analytics.
Itll also help if youre confident in what you say.
If your boss asks questions you cant answer, say youll find out what they need to know and get back to them.
Taking that approach shows youre careful yet persistent.
Bio: Kayla Matthews discusses technology and big data on publications like The Week, The Data Center Journal and VentureBeat, and has been writing for more than five years.
To read more posts from Kayla, subscribe to her blog Productivity Bytes.
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