We are now living and working in the digital age. Unless your company’s executives believe your business can survive off the grid, they must take steps toward transforming your company into a digital enterprise (i.e., a business that leverages big data to its best advantage). Data is now considered the most valuable resource in the world and successful companies know how to get the most out their data. Extracting value from data requires a company to invest in advanced analytics capabilities. If your company hasn’t invested in advanced analytics, tech journalist Kayla Matthews (@KaylaEMatthews) has a few suggestions (discussed below) about how you can convince your boss to make that investment.[1] She cautions it may take patience and “more than one serious conversation with your boss to convince them to give the nod of approval to [invest in] data analytics.” That’s probably true because a boss who hasn’t already invested in big data analytics is probably pretty stubborn about doing things the way they’ve always been done.

Convincing the boss to invest in advanced analytics

Matthews recommends doing six things in your efforts to convince your boss to invest in advanced analytics. They are:

1. Use Accessible Language. Your boss won’t buy what he or she can’t understand. Matthews cautions, “Resist the urge to pepper your pitch with highbrow language. … Keep your words and tone down to earth as much as possible.”

2. Focus on the Competitive Advantage. All corporate executives understand the language of profits and competition. Matthews writes, “Competition is a topic business leaders intimately understand. They know that an inability to compete often results in companies shutting down or encountering intense struggles in the marketplace.” She cites the findings of a NewVantage Partners survey that found around 90% of the respondents “viewed technology investments as necessary to transform into agile and competitive businesses.”

3. Understand Your Boss’s Motivations. What motivates you might not motivate your boss. You must structure your arguments accordingly. Matthews explains, “You can facilitate things — and increase the odds of your boss deciding in your favor — by taking a cue from salespeople. Spend time to understand the motivations that drive the person of authority.”

4. Emphasize That Analytics Tools Could Make Data More Accessible to Everyone. Today’s cognitive technologies, like the Enterra Enterprise Cognitive System™ (AILA®) — a system that can Sense, Think, Act and Learn® — use natural language processing so users don’t have to be data scientists to extract value from data. Matthews writes, “If your boss feels that analytics would make the company’s 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.” You could also explain that corporate alignment is easier when data silos are eliminated and all areas of the business have access to the same information.

5. Cite Statistics Whenever Possible. The late British prime minister Benjamin Disraeli is often credited with stating, “There are three kinds of lies: lies, damned lies, and statistics.” Nevertheless, statistical facts can be persuasive. Matthews writes, “It’s 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.”

6. Talk About the Things Your Boss May Miss Without Analytics. Every boss must make decisions (including about whether to invest in advanced analytics). Cognitive technologies were developed to augment human decision-making (i.e., developed to help the boss). Matthews writes, “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. … 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 they’d likely be without such technology.”

Set your data team up for success

Once the boss is on board, you want to ensure he or she isn’t sorry for following your advice. Allison Hartsoe (@ahartsoe), chief executive officer at Ambition Data, cautions, “The value of data for analytics is undisputed in today’s business environment, but not all companies use it well.”[2] She believes you can avoid that unfortunate situation by embracing seven fundamentals. They are:

1. Use language people understand. Hartsoe reminds us not everyone is a data scientist. Most people just want insights not explanations. To that end, Hartsoe suggests, “No jargon. Ever. I actually test my big presentations in front of my nine-year-old. If he gets it then I’m good.”

2. Use both data miners and subject matter experts. Hartsoe writes, “Data miners tend to interpret the data without enough SME context. This means they may not know what’s reasonable. The best case is either training SMEs to become data miners or embedding your data miners in the business.”

3. Give people the insights they need. Hartsoe writes, “Don’t play games. Just take a stand and tell your stakeholders what to do.”

4. Use a single source of truth. As noted above, corporate alignment is much easier to obtain when everyone is working from the same set of data. Hartsoe explains, “You need a tech to pull the data together, business SMEs to refine it, and ideally, the CFO’s office to bless any connect to cost or revenue if you’re going to get real impact.”

5. Start with Business Value. Like any technology, advanced analytics are only valuable if they provide a good return on investment. Hartsoe writes, “Where value is lower costs through optimization or efficiency, increase growth by finding rich new types of customers or reduce risk through stronger predictive modeling. Problems worth solving trace their roots back to these fundamental business drivers. But understand, this is an iterative process of learning and trying based on data.”

6. Democratize the Data. Democratizing data doesn’t mean everyone gets to play with it. It means everyone has access to meaningful analytic results. Hartsoe writes, “Bake your data into business-ready cookies and then monitor how much [your employees] eat. Consider teaching some more advanced skills and certifying higher levels of access.”

7. Message Your Data. Hartsoe suggests providing something like a user’s guide to explain data results. She writes, “This is particularly relevant for companies who are required to share data publicly. Get ahead of the story and protect the data.”

Hartsoe believes if you nail these basic fundamentals your boss will never regret investing in advanced analytics.

Concluding thoughts

Bosses understand the importance of decision-making. Bain analysts, Michael C. Mankins and Lori Sherer (@lorisherer), assert if you can improve a company’s decision making you can dramatically improve its bottom line. They explain, “The best way to understand any company’s operations is to view them as a series of decisions.”[3] They add, “We know from extensive research that decisions matter — a lot. Companies that make better decisions, make them faster and execute them more effectively than rivals nearly always turn in better financial performance. Not surprisingly, companies that employ advanced analytics to improve decision making and execution have the results to show for it.” Lex Boost (@aeboost), CEO of Leaseweb USA, adds, “Effectively implementing fast data processing will ensure your company is more up-to-date and relevant, and this is extremely important given how diverse data is becoming — a factor that gives us all the ability to analyze more innovatively.”[4]

Footnotes
[1] Kayla Matthews, “How to Sell Your Boss on the Need for Data Analytics,” KD Nuggets, August 2019.
[2] Allison Hartsoe, “Seven fundamentals to set an analytics team up for success,” Information Management, 4 May 2018.
[3] Michael C. Mankins and Lori Sherer, “Creating value through advanced analytics,” Bain Brief, 11 February 2015.
[4] Lex Boost, “The Power of Crunching Big Data Effectively,” Inside Big Data, 31 March 2019.