Since time immemorial, human beings have puzzled over, and been fascinated by dualities: yin and yang, thought and action, strategy and execution. As CEO of Visier, a company that helps business leaders use data to answer critical questions, the dynamic that I find myself ruminating about most is management and analytics software.
Philosophy aside, business leaders face a very real challenge: when it comes to upgrading your management and analytics solutions, which one do you implement first? Management software focuses on operations—getting things done, while analytics software focuses on insights—finding better ways to do things.
It’s the classic chicken-or-egg dilemma: management solutions require strong analytical insights to be efficient, and analytics solutions require smart operational software to generate enough reliable data in the first place.
Like yin and yang, you can’t have one without the other: they’re both essential, complementary, and interdependent. But you still need to prioritize one over the other.
The answer is analytics, and here’s why.
We’ll break down the yin and yang of both, consider the pros and cons of prioritizing each, and show you why I believe the scale weighs in favor of analytics.
How management and analytics are the yin and yang of enterprise software
Management solutions, like SAP, Workday, ADP, are operational. It coordinates day-to-day tasks—issuing invoices, routing logistics, compensating employees.
In essence, management software takes an object (a thing, e.g., bills, invoices, inventory) and applies an event—an action—to them (e.g., paying the bill, issuing the invoice, shipping the product). At scale, management software applies several events to several objects, but it’s still the same process. It’s all about effecting change and taking concrete actions.
Analytics software is the exact inverse. Rather than operational, it’s theoretical. Rather than day-to-day, it considers long-term changes. Instead of executing an event on an object, analytics takes the sum of all events on all objects to find trends, patterns, and business insights.
While management is all about action, analytics is all about forethought and decision-making. The former automates processes, and the latter helps you create new ones. One accelerates workflows, and the other shifts paradigms.
The two complement each other beautifully, but business leaders have finite resources and need to put one before the other. Upgrading your enterprise systems is an enormous endeavor that routinely takes multiple years and millions of dollars—for most companies, launching both at once isn’t realistic.
Dealing with the dilemma: pros and cons of starting with management or analytics
At first blush, it seems like you could make a strong argument that either one should be upgraded first.
If you start with management, you can start automating processes without waiting. After all, this is where your business really makes its money: getting things done. If that happens more efficiently, it could provide a revenue boost, increase productivity, and lead to eventual growth. It sounds like a win-win: your team can give itself a head start on an elaborate change management project and start seeing more output in the short-term.
But let’s consider the cons: without strong analytics, you’re flying blind through your management upgrade. You could be automating inefficient, outmoded processes. While you’ll see a short-term gain, you’ll be crippling your efficiency over the long-term.
It’d be like using modern technology to accelerate centuries-old processes. You could use a car to deliver an urgent message to the office 200 miles away: yes, it’d be much faster than traveling by horse, but you could send an email to deliver the message instantly. You could use a calculator to add up your P&L statement—it’d be faster than doing the arithmetic by hand, but you could also use an advanced software solution to do it a hundred times faster.
Now what if you were to prioritize analytics? You’ll be able to make strategic changes that increase efficiency, rather than just accelerating the old ways. Any insights you gain from a robust analytics solution can reshape the way your business does everything—from forecasting talent trends, to discovering new markets, to finding more cost-effective vendors.
Of course, the con is that analytical insights are predicated on having data in the first place. If you don’t have modern management solutions, your data could be insufficient, incomplete, or inaccurate—meaning you’d be drawing false conclusions.
Why prioritizing analytics software is the smarter choice for most business leaders
On closer examination, the scenarios above present a false choice. In reality, there’s no major enterprise that’s starting from scratch—you surely have rudimentary management and analytics solutions already in place, at the very least. In other words, businesses already have stockpiles of rich data that’s ripe for analytical insights. The best analytics solutions, like Visier, can understand and process data from legacy management systems.
But perhaps the better reason to prioritize analytics is risk avoidance: it’s simply too risky to start with management software without the latest insights. For example, moving to a solution like Workday from a handful of legacy HR management solutions is a huge undertaking. It takes millions of dollars, thousands of hours, and several years to complete. No business can afford to get it wrong and restart that processes once they have better insights.
Beginning with analytics has several benefits over process automation.
First, you can retain all your data from the old management system before collecting new data from its eventual replacement. Today, a company’s data is among the most valuable proprietary property it owns—scrapping years of data by prioritizing process automation is a huge waste.
Second, analytics allow you to discover a higher level of efficiencies. You’re not just doing the same old things faster, you’re finding fundamentally new ways to do things.
Finally, when you do eventually upgrade your management system, you’ll be able to do it much more effectively with the latest insights. You can accelerate smarter processes and design the transformation roll-out more intelligently.
It’s true that you can’t have one without the other: action is aimless without analysis, and analysis can’t be done without information about prior action outcomes. But I firmly believe it’s better to look before you leap. By gathering all the intelligence and insights first, you can be confident that your actions will be more effective, efficient, and successful.
This article first appeared in Predictive Analytics Times.