By Neil Raden
There was a time when computers were too slow to do more than bookkeeping and other back office chores. Without machines to interfere in their interactions, people performed office work like a ritual. There were set hours, dress codes, rigid hierarchies, predictable tasks and very little emphasis on change from year to year. Nothing moved very quickly. Good companies were stable and planned thoroughly. That was then. As computers slowly became more useful, necessity and market forces applied them to increasingly more critical tasks. By the 90’s, Total Quality Management, Process Reengineering and headcount reductions driven by the brutal pressure of corporate raiders forced organizations to look at the efficiencies that could be gained by streamlining business processes. After more than two decades of tireless cost-cutting and pursuit of efficiency, the relaxed and personal office life depicted on television of the Sixties was gone forever. Today, we operate Netlix-style, on-demand.
The critical mass for an on-demand world is composed of Information Technology elements such as, ubiquitous communications (the Internet), open standards and easy access. In an information business, speed is king. For an organization conducting business, managing a battlefield or monitoring the world’s financial markets, going faster means a shift from a reliance on prediction, foresight and planning to building in flexibility, courage and faster reflexes, catching the curls as they come and getting smarter with each thing you do (and making your partners smarter, too), ranking the contingencies instead of sticking to the plan no matter what. But what exactly is speed?
Speed implies more than just doing something quickly. For example, being able to load and index 10 billion records into a data warehouse in an hour is one measure of speed, but if the process has to wait until the middle of the night, or it takes another day to aggregate and spin out the data to data marts before it can be used or if the results have to be interpreted by multiple people in different domains, then the relevant, useful measure of speed is the full cycle time. In Six Sigma terms, cycle time is the total elapsed time to move a unit of work from the beginning to the end of a physical process. It does not include lead time. Measuring speed can be relative or absolute. Closing the books in three working days is absolute. Being first to market is relative.
There is a paradox of efficiency – investing in efforts to pare the time it takes to complete work steps can often lead to even longer cycle times. Consider scheduling aircraft. When a step is delayed or fails, there are people to consider – passengers and crew, for example. The efficiency of the solution vanishes when something doesn’t work or when the means loses sight of the desired result. Perhaps the process is very efficient, but brittle—when it breaks all prior gains are lost. The lesson is that speed can’t be measured by the speed of steps or by the speed of a sequence of steps. People are always involved, often, people tangential to the process. The Concorde cut Paris-to-New-York flying time in half, a savings of three and a half hours, but in today’s congested surface traffic and extreme security, a 3.5 hour flight could still take 8 or 9 hours door-to-door, a savings of only 25% or less, possibly not worth the 300% fare increase, except for the most extremely time-conscious.
In the workings of decision-making in organizations, gaining speed can not be limited to the automating of single tasks or optimizing individual productivity. Speed has to be an organizational concept. The actors need to understand the priorities and not waste time trying to optimize things that aren’t important. But one area that is in desperate need of work is organizational decision-making.
Knowing the Enemies of Speed
What are the enemies of speed? Today, much of analytics is a solitary effort with highly skilled and trained workers expending a significant amount of their time re-configuring data, or waiting for others to do it as aspects of the problem space change. While one group expends a considerable amount of time developing reports, another group pauses to re-format the reports or, more typically, either re-key or import some of the information into their own spreadsheets. Spreadsheets, though an effective tool for individual problem-solving, cause delays when others have to interpret or proofread spreadsheets authored by others. The problem isn’t limited to spreadsheets – it applies to varying in degrees to all types of analytical software, but the spreadsheets account for the overwhelming proportion of problem.
And Big Data trickle-down will only make the problem worse.The gap between the first analysts (data scientists) and decision-makers is getting wider.
When information from analytic work is communicated to others, the results are often difficult to explain because they are conveyed in summary form, and usually in aggregated levels, statically. There is no explanation or explicit model to describe the rationale behind the results. These additional presentations about methodology, narratives about the steps involved, alternatives that were considered and rejected (or perhaps just not recommended) and a host of other background material, usually presented in a sequence of time-consuming, serial meetings that have to be scheduled days or weeks in advance are the greatest enemies of speed today. They turn cycle time into cycle epochs. The reason for all of this posterior explanation is the cognitive dissonance between the various actors. The result is that well-researched and reasonable conclusions are often not actionable because management is not willing to buy in due to their lack of insight into the process by which the conclusions were arrived.
The solution to this problem is an environment where complex decisions that have to be made with confidence and consensus can gather recommendations to be presented unambiguously and compellingly across multiple actors in the decision making process.
The late Peter Drucker said that information was “data endowed with relevance and purpose,” but it takes a human being to do that. Unfortunately, one person’s relevance is not necessarily another’s. The process of demonstrating to others what you’ve discovered and/or convinced yourself of can add latency and frustration to the process. The generation of mountains of fixed reports and even beautiful presentations of static displays such as dashboards cannot solve the problem. Henry Mintzberg wrote repeatedly that strategy was never predictable; it was “emergent,” and based on all sorts of imperfect perceptions and conflicting points of view. The lack of confidence that each actor has in every other actors’ methods and conclusions is a serious enemy of speed. It is the cause of endless rounds of meetings, delays and subterfuge.
Cost-cutting will always be a useful effort in organizations because inefficiency will always find a way to creep back in, but the dramatic improvements are largely over.The real battlefield today is differentiation, distancing your enterprise from your competitors. And in an era when every company potentially has access to the same level of best practices and efficiency, the key to leaping ahead is speed. Finding a new insight, a disruption or a discontinuity before anyone else, and being able to act on it, is the ticket to the show. Organizations need to be constantly on the lookout for new ways to streamline, to enhance revenue opportunities, to improve in a multitude of ways, to go faster. Faster decisions, faster to market, faster to understand the environment, faster to go faster. Making things go faster or better is rewarding, but giving time back to people is crazy fast, it is supercharged. The one resource that is in shortest supply is the time and attention of your best people. Give some time back to them and you can change their world.