Sometimes it seems to those of us on the outside that big corporations with big data collection and analysis functions just “are”, which they always have been. That, of course, is not true. Every company, regardless of its current size, had to evolve its data capabilities. Even your business today may have some basic data collection and analysis capabilities.
It is useful to create several “stages” of this data evolution. We do this for a couple of reasons. First, it’s important to have a scale, a growth chart, if you will. This scale lets you know where you stand in relation to complex data collection and analysis organizations. But we do this for another reason as well. At different stages of this evolution, companies have different capabilities. We want to classify these capabilities so that any company, regardless of its stage in the data evolution process, can take advantage of data-driven processes.
Stage 0. Little or no data collection
Of course, everyone has to start at the beginning. Initially, companies collect little or no information about their processes. Every company has some data: basic accounting data is necessary to stay afloat. The Stage 0 company is characterized by two criteria:
1. The Stage 0 company does not have much data beyond accounts payable and receivable, and
2. The Stage 0 business recreates the data when needed to answer a business question instead of collecting it up front.
In other words, the Stage 0 company collects little to no information on an ongoing basis. This is not to say that a Stage 0 company does not know its business. Rather, to be successful, any business needs to have a good sense of sales cycle times, the type of prospects most interested in buying, the products or services that are most profitable, and approximately how much they should charge for those products. . and services.
But that’s different than asking what the sales cycle times were for the last 5 sales. Or the last 50 sales. Or asking what was the profitability of the last 50 clients.
Also, many companies are able to decipher this information from records, recreations, and research. But the Stage 0 companies have not collected this information. in advancepreparing to answer such questions before they are asked.
If you identify yourself as a Stage 0 company, that’s fine. Don’t worry, you’re in good company. Being a Stage 0 company doesn’t mean there aren’t opportunities for you to take advantage of data-driven business approaches. In fact, this book will describe very specific things you can do today to start turning your business into a data-driven business.
Stage 1. Basic reports
Companies that collect data often report on it. The Stage 1 company generates this basic analytical tool: the report. To be clear, a report is simply a summary of the data collected, perhaps even some basic statistics behind that data, such as averages, totals, minimums, or maximums. These are very common in most businesses: Sales Activity Reports, Lead Summary Reports, Sales Forecast Reports, Cash Flow Reports, Manufacturing Reports, etc. The Stage 1 company, however, is characterized by the lack of formal analysis of these reports. In other words, the interpretation of these reports is left to humans.
Now, there is nothing wrong with the human interpretation. In fact, humans can sometimes see patterns in data that computer programs can’t find. The important criteria of a Stage 1 company is that there is nowhere else for this data to go.
Of course, there are many opportunities once the data is collected and stored. In this book, we’ll specifically discuss the next steps Stage 1 companies can take to use the data they have.
Internship 2. Trends and Forecasts
Once enough data is available and a company has the right tools in place, historical data can be used to help find patterns and potentially predict future results. The Stage 2 company uses your data to forecast trends and predict outcomes.
To be clear, these rankings and predictions happen in an automated fashion with calculations and procedures. It is not enough for a Stage 2 company to rely on human interpretation alone. A Stage 2 company can tell you what the sales forecast is for next week, along with a margin of error about how confident they are in that number. They can tell you how long it takes to process an order or how much time will be spent on service or installation.
To know this, the data must be collected over a reasonable period of time. How long is reasonable? Well, that depends on your industry and the type of business you do, but later in the book, we’ll cover some ways you can guess how long is “long enough.”
A Stage 2 company becomes very good at predicting results. They are often not surprised by the regular ups and downs of business, because they have been following “normal” for some time. But as good as the Stage 2 company is at predicting results, they can’t seem to influence them regularly. That is where our next stage comes in.
Stage 3. Infer and classify
It’s one thing to know that you’ll sell 100 widgets next week. It’s an entirely different thing to know that if you drop the price by 10%, you’ll sell 150. The Stage 3 company knows this because it uses its data to infer relationships and rank influences.
Inferring relationships requires that we go beyond predicting outcomes and study the inner workings of why things happen. What makes our sales figures go down in November? Which customers are likely to pay the most for our product? What combination of product, line, and personnel creates the greatest probability of delay in manufacturing time?
These questions require us to compare data with other data and see if there is a connection. Over time, a Stage 3 business can tell you not only who its most profitable customers are, but also why. And they can use that information to find other, more profitable customers.
The Stage 3 company can produce influence lists of its results, or key factors. These key drivers can influence numeric results, such as profit, or non-numerical results, such as: did they buy or not? These key drivers help guide decision making. When a senior leader or executive makes the decision to orchestrate a strategy, the Stage 3 company can use these key drivers to get a sense of how results will react to that new strategy. Why can they do this? simulation it is often a key decision-making tool.
However, a human being is still using instinct to guide his strategy. True, with a list of key drivers and an idea of how they affect your business, you can simulate different strategies and see how they will work. But can you simulate each strategy to see which one is the best?
A simple example will demonstrate how difficult it becomes. Suppose you are a clothing company that makes 3 styles of shirts and 3 styles of pants. The shirts and pants come in 3 different colors and 3 different sizes. You only have one manufacturing process for clothing, and you need to decide how much time to spend on each style of shirt, pants, color, and size before modifying the process for the next. And of course, each style of shirt and pants has a different level of profitability associated with it. Oh, and you can’t make enough of everything to keep up with the demand; you will have to pick and choose.
Even if you know exactly how many shirts and pants will sell and for what price, with all the different combinations of shirts and pants, colors, and sizes, and the profit trade-offs between them, how do you test each combination?
Those with a bit of math background may recognize this setup for a type of math problem called “optimization.” This type of problem is routinely resolved by our last stage of the company.
Stage 4. Optimization
Optimization is the idea of getting the most (or the least) of any outcome you want: usually profit. The Stage 4 company can find the maximum or minimum of what it wants by analyzing all the possible scenarios that may influence its results.
For example, in the above situation, a Stage 4 company can tell you exactly what combinations of shirts, pants, sizes, and colors will maximize their profits, given the constraint they have on the manufacturing process. They can also tell you exactly what price to charge and which customers to target and when. They can tell you which processes are most likely to meet your strategic goals: reduce costs, increase innovation, or increase the bottom line.
It is true that to achieve optimization, you need to have a good set of tools, good data, and good skills. But that doesn’t mean you have to be a Fortune 100 company. Even small businesses can use tools to optimize their processes with very little data, as long as the infrastructure is in place to measure response and gauge their ongoing efforts.
in evolution
You probably have a good idea of where you fall on the evolutionary spectrum. Obviously, it is very likely that your target will move on to the next stage. That’s really what this book is about. We’ll explore what it takes to evolve your data-driven decision making to the next level. In this book, we will focus primarily on sales and marketing. In other books, we’ll cover topics like operations, talent acquisition and retention, and research and development.
Evolution requires two things: infrastructure and support. Infrastructure comes through knowing what data needs to be collected and how it’s going to be analyzed. Support comes from having the right people driving the organization to do things slightly differently than they did before.
It is important to note that in almost all surveys of companies going through a process to become a more data-driven organization, the number of car keys of success is executive support. Without it, it is almost impossible. With it, things tend to fall into place as long as the infrastructure is available.
As we look at the elements of a data-driven sales and marketing function, we can outline the infrastructure. We can even point out where executive sponsorship can influence the process, but obtaining and maintaining executive sponsorship is your responsibility. And it is critical.
It is important to note that even if you have evolved past stage 0, it may still be important to read the sections on earlier stages. Who knows? You may learn a thing or two that might help along the way. Each of the stages is meant to develop itself, so it’s not completely irrelevant to where you want to get to.