Archive for 2010
Tuesday, December 21st, 2010
You need this style today. You probably do not have it. Thirty years ago, statisticians starting using regression to improve response rates to direct mail campaigns. Ten years ago, artificial intelligences (AI) academics discovered new (and old) approaches to predicting the future. Five years ago, businesses saw the benefits and started incorporating future-looking analytics into the environment cost effectively. One year ago the recession hit and everyone said they were surprised (well, except a few people).
Predicting the future is hard. At the economic level it is really hard. But predicting the future at a customer level, while hard, is a much more bounded problem.
The Future Style of analytics uses your corporate customer data (touchpoints, surveys, purchase transactions) and combines with it with any other available data such as demographics, firmagraphics, behavioral and attitudinal to create a prediction. Perhaps you need to predict when a customer will churn from their cellular company, when a customer will fall into quiet mode for their DVD rentals, what they may need or want to purchase next or when they will move from the student segment to the affluent segment.
The Future Style gives you predictions at all levels, then helps you anticipate changes and provides a window, sometimes small, to do something about it. It’s up to you to act.
The Future style is not easy. It never is.
You need a large amount of past historical data. You have to assume that past behavior can reasonably predict future behavior. You also need the right math and science working on the data to make the prediction of the future with confidence. You need to take into account all of the variables that you think could influence the prediction. That’s a lot of machinery, a lot of infrastructure. It takes a coordinated effort to make this happen well, happen quickly, and most importantly integrate it into your business process.
Lets face it, if you can predict the future but can’t do anything about influencing the present to make money, there’s no point. Stop wasting time. The biggest, and I mean the biggest, issue with the Future Style is using a prediction to take action today. A lot of clients have spent their money to create a Future Style capability but they could not get their “customer channel” to change their business process and the way they interact with the company’s customers (despite my best efforts to address this with them). I said “company’s customers” because if your SBU or functional group believes they own the customer, you have to work with them (or go to the CEO) as a partner to implement actions to make the predictions valuable. That’s hard. Maybe it should not be hard, but it is.
The key to the Future Style is, yes, to have the capability to predict but also the ability to intervene to your benefit.
Analytically enabled agile companies balance all three analytical styles and use them where needed. Knowing which style to invoke in which circumstance means knowing what you want to measure—back to our strategy once again. The other necessity for analytic enablement is to have the information infrastructure behind you to support flexible, reliable and efficient access to the data and an ability to manipulate it for insight.
In the next series of blogs, I will look at what it takes from the technology perspective to be an analytically enabled agile enterprise.
Category Agile Analytics, Agile Business, Blog, Gregory Lampshire | Tags: agile companies, analytical styles, analytics, attitudinal data, behavioral data, customer data, demographics, firmagraphics, future style,
Friday, November 12th, 2010
I was walking down the main street in my town the other day and I was struck by how many signs there were. Signs advertising places of business, places to eat, drink, have fun, buy things, get broken things fixed… the signs were endless. Many were advertising the week’s specials: buy now and save 20%. Each Sunday, I receive a stack of advertisements for the week. I also receive daily emails from merchants with that day’s special deal or a special thought about how to do something. On occasion, I receive a text message with an advertisement. When I go to work, I like to look at my operational reports—the status of my client projects, whether they are falling behind or are ahead of schedule.
All of these scenarios speak to the Real-Time Style. What real-time means is dependent on the business process and the receiver (in the examples above—me). Real-time sounds cool, it sounds hip. I’m real-time, you’re real-time.
In some cases, Real-Time Style means I get a text message as I am walking down the street. Sometimes it is a weekly flyer on Sunday since I do a lot of my buying on Sunday. Sometimes real-time means that as I am talking to a customer service rep, predictions are being made about how valuable a customer I am using information recorded on the call–then deciding how to tier me so I get the right level of service–not too much that I become unprofitable and not too little that I churn or attrite.
Real-Time Style is very contextual: Where I am or what I am doing when I make a decision makes a difference. This is important.
If the Real-Time Style has one critical element to be successful, it is that real-time analytics must have a context in which to make decision. If you need to build the infrastructure to have real-time analytics, and it is not always cheap or easy, then the target of the analytics, whether an executive, a manager or a customer, has to be in a state where a decision can be made. Imagine the entire company, completely organized behind influencing the decision of a single customer or person at an instant of time. If you use this customer-centric view, you will instantly realize the incredible amount of organization and collaboration to do this successfully.
This idea of the “context” actually gives us the definition of Real-Time Style: analytics designed to influence a decision within a specific context at the point of decision making.
Breaking down what a person does into smaller steps is key. Knowing how decisions are made and where they are made is paramount. What is your customer lifecycle? What does a customer service event look like? You have to take that person’s view, then align your analytical capabilities to support it. If you want to target a person and influence them, those capabilities are the “wood behind the arrow.”
Coming next: the third and final analytical style, the Future Style.
Monday, November 1st, 2010
The Operational Style is the bread-and-butter analytical style of companies today. The Operational Style tells you what happened. If you do not know what happened, it’s hard to set expectations about what will happen.
As I mentioned before, most companies today are dominated by the Operational Style. Managers need reports on financial status, teams need reports on quality measures, HR needs reports on performance to assign bonuses or promotions.
Most operational reports are fairly simple. A matrix of numbers. You have columns and rows. The intersection between the two is a number or a color or an indicator of some aspect of your business. The problem then becomes what to do when you have a lot of columns and rows, a lot of operational data. No problem—our technologist friends then created the cube. Take a column-and-row report and add another dimension, say time. Or by state, by customer segment or by SBU. Then add 10 more dimensions. That’s a lot. Let’s face it, your operational systems collect an enormous amount of data and there are almost limitless ways you can slice and dice the data.
The Operational Style is basic. You have to get this mostly right—not perfect, but good enough to run your business. The key challenge in the Operational Style and the key aspect to enable within this style is to make all of this information more easily accessible and easier to use. Technologists have invented many new software products, some fairly expensive, to help you move through and explore the data. Some managers, for example, just want their weekly operational report as a link in their email (or an Excel spreadsheet). They want weekly bursting. Some managers want the ability to zoom in and out, scan up and down the dimensions, to understand the different relationships between the information. This is the key part of this style.
The Operational Style needs to support simple analytical consumers as well as explorers.
Most people are analytical consumers. Give me the information that I need to do my job. I’ll watch the numbers. Explorers go looking for information and relationships. You need both in your organization and you need to support both using the same data so that the numbers that the analytical consumers use match the numbers that the explorers use. If you do not make the analytics tie out, it’s hard to believe the numbers.
Tie-out does not mean that you need to have all the data in one database and only use one analytical application—that’s actually against agile principles. It does mean that you need to create layers of capability that reinforce tie-out. You need one version of the truth, but you need one version of the truth that is flexible. Most companies take “one version of the truth” to mean something big and consolidated, when in fact it’s a business concept that expresses a need. That need can be satisfied multiple ways, and in some cases, much more cheaply than others.
Next up: The Real-Time Analytical Style.
Wednesday, October 20th, 2010
I’m describing the three main attributes of an analytically driven, agile business. Let’s assume you read my last blog, “#2: Culture of integrating quantitative and qualitative into business decisions.” Now it’s time for the third key trait.
#3: A balanced analytical style
What is an “analytical style”?
When a company needs to use analytics to be agile, it often needs to calculate numbers. Most companies have finance systems and financial reports. Most manufacturing companies have operational systems, such as manufacturing execution systems, to run machines and tooling. Most insurance companies have claims reporting systems to report how many claims were adjudicated and the cumulative medical-loss ratio. Got it.
But what if you need to run an experiment or test an hypotheses? What if you need to forecast what will happen using predictive analytics? Where’s your capability to do that?
A balanced analytical style is a capability in which a company uses analytics to address different levels, different speeds, and different calculations at the same time and can choose the best approach to meet the business process need. All companies today have a mix. How good they are at balancing the mix can mean the difference between marketplace success or failure.
What are the different styles and why do they matter? In the analytics space, there are three dominant analytical styles. Balancing the mix improves agility because different styles are needed to serve different customers, products and channels. Since the market is always changing, rebalancing the mix is needed, sometimes frequently, sometimes less so. To be agile, you need the capability to find the balance and rebalance quickly and cheaply. It’s always changing.
The Operational (Retrospective) Style. The Operational Style dominates analytics today. It tells you what happened. This analytical style includes financial status, operational reporting, facts and data that help you run the business. The challenge with the Operational Style is making this information more easily accessible and easier to use.
The Real-time Style. Real-Time Style is an analytics process designed to influence a decision within a specific context at the point of decision making. It tells you what is happening now and enables you to respond in near real-time with an appropriate action. We see this when a call center agent can respond on the fly to new information you’ve provided in an interaction.
The Future Style. The Future Style of analytics looks at a variety of sources of information and intelligence and applies sophisticated modeling to predict what will happen next. The realm of predictive analytics, the Future Style anticipates changes and provides a window to act proactively.
In future blogs, I will examine each of the three analytical styles in more depth and speak to how they can be used in a strategy that blends them.
Closing Comments on the Creating the Analytically Enabled, Agile Company
Is your company analytically enabled? To some degree they all are. Do you have the right mix? It takes more than technology: it takes a strategy, it takes a desire and the capability to experiment. It takes a balanced analytical style. You need all of this to be successful. The right mix, the right balance, the right ways to implement it are hard to get right. Start now.
Monday, October 11th, 2010
Tracy Cather addresses how the rise of cloud computing is changing the way companies use their information through business intelligence and analytics.
WATCH NOW>> Tracy Cather on B-Eye Network
Category In the news | Tags: Agile Analytics, Ajilitee, B-Eye Network, business intelligence, Business Intelligence Network, cloud computing, HP, Information Management, Knightsbridge, Ron Powell, Tracy Cather,