For some organizations the title might not be too meaningful, but it is meant to emphasize a conceptual point. The managers in an organization do the managing. They do this at least theoretically by managing resources – including people. Then in the end, if fortune is smiling, the markets will adhere to the game plan, and the company will succeed. However, companies routinely fail, creating products and services that the markets don’t care to purchase. They sometimes use methods that don’t agree with the needs of the market – perhaps operating for decades totally disassociated from the reality of their changing market. So I hope readers appreciate the general concept: although the markets don’t manage companies in a literal sense, perhaps in an abstract sense they should. The question is how – and what different roles people have to play to enable the shift in paradigm.
In my previous blog about the “Wrongness of the Nogs,” I said that people tend to internalize their success: “I am successful. I am a success.” They associate their success with their intrinsic attributes. It is the result of something special inside them. They are less likely to externalize their success: “I was at the right place at the right time doing what comes naturally.” Whether in reference to a person or company, this blog is not about the individual that is intrinsically successful: i.e. the success is genuinely from superior design, a winning formula, or a fabulous way of doing things. This blog is for the rest of us who must accept the circumstances and context of success. The boundaries of interaction between the organism and its environment represent a major consideration: i.e. in operational terms, the market tells us or give us signs of our level of success or failure. Yet those that control resources in the organization might make use of metrics that disagree with the market.
Consider an example. A police department decides to drastically reduce spending by cutting the number of officers. The department also intends to use efficiency and performance improvement programs to improve service. The chief says, although it is true that staffing is being reduced, services levels will remain about the same through the sophisticated use of metrics. This example has a bit of joke which I will explain in a moment. Rather suddenly there is a sharp increase in shootings and murders in the city. The metrics, although it is true that they seem indicate a certain aspect of service, appear to provide little or no guidance in terms of controlling and reducing the shootings and murders. Here is an example of a management regime managing resources in a manner that is alienated or disassociated from reality.
My joke is that I work with all sorts of metrics to improve employee performance. This blog is not about my workplace, I should say flatly. But when I work with metrics, I routinely take into consideration the likely disconnection that exists between the management function – i.e. keeping the organization running smoothly and efficiently – and the markets. The market has the ability to throw all of the management efforts out the window, changing what seems like an asset into a liability. Keeping the ship “on course” or at its present direction isn’t necessarily a good thing. In fact, it isn’t a thing at all. It is irrelevant. The purpose of the voyage is to reach the destination. For many companies and I imagine for humans too that destination is elusive and constantly moving. Most organisms on the planet are products or survivors of change. Either we change with the times, or we die trying. We could also die without trying. But like I said, survivorship dynamics made us into what we are. Our interaction with “the market” defines who we are and whether or not we persist.
So back to the police department that recently cut staff and implemented an alienating metrics regime. I want readers to think about this carefully, because the suggestion is a bit radical. Which individuals in the police department are probably most familiar with shootings and murders in the city? It is true the person gathering stats has a statistical understanding of the situation; but this individual likely doesn’t have the foggiest idea about the difficult-to-quantify-but-nonetheless-critical lived experiences of residents. The police officers likely have the greatest amount of intellectual capital. But they are not normally used as a source of guidance for management. This is not to say that management necessarily ignores its workers: the lens merely tends to be tiny. It is an instrumental lens – meant to achieve particular objectives.
I recall hearing on local radio about a pilot program for community policing in Toronto – where officers would live and stay within particular communities for many years. Gun and gang violence has risen sharply recently. So I admit that my “example” in this blog is not entirely fabricated. For some people, community policing is mostly a public relations exercise. But actually, if handled to gain intellectual capital, the underlying “placement of ontology” could be shifted away from managers and brought closer to communities. This could also be regarded as a power shift, because the decision-making infrastructure would likewise be repositioned. I am not saying this would occur in relation to physical buildings but rather in relation to the data, which would become more community oriented.
Routinely do established frontrunners in an industry become threatened and overwhelmed by recent entrants. Due to the pervasive tendency to dismiss the perspectives of workers, there has become no need to hire workers that effectively rationalize, conceptualize, and convey the needs of the market. Workers are hired for their compliance and conformance. When they interact with the market, conveyance flows from their managers to the market, which is likewise expected to comply and conform. But it won’t. The company like many organisms incapable of adapting to change – like some people that find themselves disassociated from reality – become competitively disadvantaged. At some point, such companies might face displacement. The public – the market – interacts with companies through its workers. Thus when deep problems arise, companies might have vast amounts of internal data (operational data) and pinholes of reality through disconnected stats that don’t actually deal with “external” conditions. In effect, the market might be silenced perhaps rather oppressively through an alienating metrics regime.
Am I part of an alienating metrics regime? I don’t think so – because I am aware of traps – things that might lead to systemic dysfunction. Change is something to embrace rather than dismiss or ignore. The challenge for me is giving voice to the market – incorporating its needs into the data. It is so easy – and in fact easier – to ignore than to take into account the market. If the objective is to persist within a given environment, its market must always be the primary participant, stakeholder, and consideration in the data. The main task of the organization is to serve its needs, which includes configuring or shaping the organization’s processes and controlling its resources; this requires that data be sensitive to the market. It is an issue of ontology. Clearly, ontology has “placement.” It can emerge from those that control resources. Or it can be from those near the market. Every organization has to decide which place of origin is subordinate to the other.
About a month ago, I was asked to develop the logistics, to administer, and follow the progress of a new performance incentive program. Many companies have performance incentive programs; so this isn’t the interesting part of the story. Without necessarily sharing too much information, I would say that I had some preconceptions about which metrics would be most useful to measure the effectiveness of the program. I have since concluded that these metrics are likely much less effective than those that I now favour. Moreover, some of those metrics that I now favour didn’t exist a month ago, or they never received much attention from me. I believe that the main metric surrounding my preconceptions – and perhaps those of the industry more broadly – involve what I would call the “success rate”: given a certain number of opportunities, in what percentage of this would an employee succeed? The question makes sense from an operational standpoint. I have found that this metric cannot be clearly connected to the program.
This is actually a good example regardless of the nature of the business or organization. There is a socially constructed perception that money can improve the abilities of people. But in all likelihood, money cannot improve their “abilities.” It can influence the outcomes of what they do with their abilities. Consequently, if a metric is designed to measure changes in ability, then incentive might not alter the metric – unless of course employees have been holding back on their abilities due to absence of incentive. On the other hand, if the ontology is shifted away from the social construct and moved closer to the market, the underlying weakness of the metric becomes apparent. Regardless of people’s abilities, the actual objective of a reward-for-sale incentive is to increase their interaction with the market and to capture as many of the opportunities available in that market. Abilities matter in order to maximize the likelihood of success. But an organization can actually become more successful without necessarily changing its success rate simply by anchoring its metrics closer to the market – that is to say, to increase the number of opportunities.
Even a lousy car salesperson can sell more cars by approaching more customers entering the dealership. Their success rate would remain lousy – although both the agent and dealership would gain more business. Now just pretend – this being a data science blog – more than just money is actually at play. The agent is actually trying to obtain data from as much of the market as possible. The agent wants to determine whether the client is interested in buying a car – the type, price range, specific characteristics. Once the data is at hand, the entire dealership infrastructure sets its wheels in motion to make things happen for the client. Why would this be? Its existence is premised on letting the market do the managing: all of the fulfilment apparatus fires up when these human tendrils dressed as sales agents spread and latch to the market to gather as much data as possible. The business is actually a data-gathering facility. It doesn’t just respond to emotionless data. It interacts with living data. There are cars on display. There are human agents to intercept data about feelings, desires, and expectations.
I return to my community policing example in conclusion. I said that some people might think of this program as an exercise in public relations. I certainly can’t argue against the general gist that “interaction is good.” Specially trained officers who can speak several languages and who might themselves reflect the ethnicity of the neighbourhood will be placed in high risk communities. Their mission is – or at least it should be – to gather living data to help make the service apparatus operate more effectively. Whether or not somebody whose role is to “police” a neighbourhood – normally involving the conveyance of authority from the top to bottom – can in certain respects learn to operate in reverse – enriching the system with data – is a big question. I certainly have my doubts of the ability of the feedback mechanism to deliver data in an actionable manner. Also unclear is the extent to which the system receiving the data is willing to shift the ontological placement or perspective of metrics so that resources are more closely aligned with the needs of the community – rather than some kind of alien management regime. Certainly when an organization has been operating for decades with clients – and yet it seems to lack the intellectual capital to serve them – this is a sign of deep and systemic disassociation. It doesn’t matter if the organization is a police department or mega-corporation. Displacement from the market has severe consequences.