Until 1933, much of the information in today’s financial statements was only available to insiders. It took an act of Congress that year to compel businesses to disclose their sales, assets, inventories, and profits. More than 80 years later, most executives probably believe they know more about their company than outsiders.
But if that’s the case, it won’t be for much longer. Technology is laying bare an ocean of data and information, and outsiders are piecing it together to develop ever more accurate, up-to-the-minute views of internal business operations. It may not be long before external sources provide faster, more accurate inside information on businesses than internal sources do.
Of course, outsiders have long tried to profit from value that’s being overlooked by leaders on the insides of their own businesses, who always still have a home-field advantage. That’s nothing new. But as the expanding array of tools changes the game, some execs aren’t adapting fast enough.
Silicon Valley is outperforming Wall Street in the race to capture this overlooked value by technological means. In the last few years, startups like Planet Labs and BlackSky Global have launched hundreds of shoebox-sized, orbital satellites that regularly photograph store parking lots, mining sites, plant smokestacks, storage depots, and distribution warehouses. This raw data captures a big chunk of companies’ external operations footprints.
Other startups aggregate, analyze, and distribute these raw data. For example, Spaceknow analyzes traffic of all of the world’s trucks and ships among mines, depots, and warehouses to deliver what they term “radical economic transparency.” Hedge fund traders can subscribe to companies like RS Metrics, which uses imaging to monitor retail traffic and predict sales at chain stores in advance of earnings reports.
Meanwhile, outsider-led investigations into the internal details of businesses is now under way. Some useful, sensitive facts are already publicly available: salaries, benefits, organization size, reporting structure. These precious tidbits are innocently sprinkled across sources like LinkedIn, Glassdoor, Vault, and others.
Regulatory filings, tax records, public hearings, court proceedings, and other sources of information–now widely available for free online–can provide insights that never used to be nearly so easy to access. And since individuals can manually assemble these scraps of data into fairly accurate, reverse-engineered snapshots of organizations’ size, performance, and other features, it’s easy from there to flesh the picture out with compensation, estimated sales volumes, and operating costs.
The real game-changer is already in the works. It won’t be long before big data applications continuously scoop up all of these bits of information and sift them through algorithms. With this level of computing power brought to bear, outsiders will be able to compare performance across a wide swath of the world’s businesses. For instance, they’ll see where sloppy management indulges wasteful work methods, a lucrative source of untapped value.
As an analogy, consider how companies like Mint gather your personal financial data and compare it anonymously to that of your peers. Banks and brokerages once tightly guarded that information. With it, Mint can now point out where your assets are performing well and where you’re wasting value. If an interest rate on a loan can be lowered, Mint will suggest alternatives. Now Imagine the same for businesses, except comparisons won’t be anonymous. No permission will be needed to publicly model and compare your company’s performance.
Half of the business world has been relatively naked, so to speak, for around a century: the part that runs on hourly workers. For generations, hourly work has been simplified, standardized, and largely automated. There are few secrets in conventional, factory-like organizations; manufacturing processes are known, and products can be reverse-engineered. Even if those companies want secrecy, the laws of physics and the capabilities of industry-wide machinery are hard to hide for long. The locations and sizes of plants in various industries are often a matter of public record. Information providers report on utilities properties, for instance, based on compilations of public filings.
But in this regard, anyway, many more businesses stand poised to join the ranks of physical industry. Soon, most of the waste and overlooked value will begin showing up in the other half of the labor force, too: the sphere of white-collar or “knowledge” work.
Workers here toil (with their minds) in departments devoted to sales, accounting, customer service, human resources, and so on. These knowledge-work “factories” are awash in the latest technology, but almost none of the work has been simplified and standardized to the degree that manufacturing operations have been over many decades. As ongoing debates over best practices hint, those processes are still needlessly complex and overwhelmingly manual–despite the wealth of digital solutions proposing to streamline them.
For two decades, my company, The Lab Consulting, has analyzed hundreds of thousands of knowledge-worker job positions across companies in more than 30 countries. On average, knowledge work organizations unintentionally squander 40% of their workers’ time on avoidable, repetitive tasks: rework, error correction, customer over-service, sales downtime, and duplication.
This waste is hard to see, because in many cases workers are making up for dysfunctional processes. They’re preserving customers and revenue that fall through the cracks. It’s just considered a necessary cost of doing business–in other words, “virtuous waste.” Still, it’s waste nonetheless, and on a staggering scale.
We estimate that the costs of repetitive knowledge-worker tasks reduced 2014 earnings for the Fortune 500 by about 12%, or $212 billion. This translates into roughly $4 trillion in overlooked shareholder value. And outsiders lust at the prospect of seizing even a sliver of it.
Even without satellites and algorithms, outsiders uncover breathtaking levels of waste and untapped value in knowledge work. For example, some activist investors are trimming knowledge workers from packaged food companies. They slash the senior ranks of product developers, market managers, and sales staff, then simply run the operations as commodity businesses.
Meanwhile, Silicon Valley has already launched tens of thousands of digitization startups. Those companies automate the manual knowledge work of entrenched financial businesses–consumer mortgages, small business loans, and insurance. In the process, they steal customers. These opportunists are known as “fintechs,” and Mint is just one example.
The shareholders of entrenched businesses would be best served if insiders eliminated waste and overlooked value before competitors or activist investors ever got started. That way, they’d have nothing to fear from satellites and algorithms. Some large banks are already restricting the flow of their customers’ information to aggregators like Mint. But that’s just a rearguard action.
Established businesses will have to see the opportunities as the outsiders do: Where are our knowledge workers squandering their time? How can we simplify and standardize their daily routines? Where are processes broken? Most of these fixes, our research shows, don’t require new technology.
They do require a new perspective, though: that of your would-be disruptor who’s just outside–or overhead, as the case may be–peering in.
William Heitman is managing director at The Lab Consulting, which helps companies implement non-technology business improvements.