Practically every large company has carefully formulated the strategic decisions it must make, but only 10% implement those decisions successfully. Moreover, 60% of the human resource and information technology departments in those big companies don’t even link their priorities or budgets to the company strategy. And 70% do not link incentive compensation to the strategy. Most important, 95% of organizations don’t tell their employees what the objectives and strategies are!
Richard E. Kouri, professor and executive director of NC State’s BioScience Management Program (Richard_Kouri@ncsu.edu), gleaned these numbers from IBM and other sources in order to illustrate:1) why it’s not surprising that so many companies fail to achieve and maintain competitive advantage, and 2) why it’s essential to build a decision-ready organization.
Prof. Kouri and others will explore these questions at the upcoming CIMS Fall Meeting, Oct. 25-27, which has “Becoming a Decision- Ready Organization” as its theme. Consequently, IMR began this interview by asking:
What do you mean by decision-ready and why is this a pressing issue now?
KOURI: A decision–ready organization is one that is comfortable with determining which decisions it should be making and then is comfortable with implementing them successfully throughout the organization. The issue seems more important now because of the huge and ever-growing numbers of changes impacting virtually al industries. The fact that over 15 petabytes of data are added to the Internet per day (and that number is growing exponentially) means that companies must be able to analyze these data, convert these data into actionable intelligence, and use this information effectively by making sure the company is decision–ready.
One of the great problems, and why we see too few decision–ready organizations, is that companies don’t often ask the right questions. They ask very general questions; e.g. how are we going to cure cancer? That’s a bit too general. A better question might be: Which biotech companies have drug candidates in preclinical testing for colon cancer, and which ones may be excellent targets for establishing partnerships in this therapeutic area?
How do you get organizations to ask the right questions?
A good starting point for decision- ready organizations is the ability to ask questions in articulate and useful ways; e.g., what exactly do we want, what problems are we trying to solve, what kind of decisions would we make if we had this information, what do we want to do with this information, or what are the key decisions we need to make over the next 60 days? If you cannot do anything with this information, then you are asking the wrong questions.
In order to create these questions, organizations must assemble people from many different functional areas, as well as people from the outside, all of whom are aware of the overall goals, strategy, objectives, and current situation of the organization. This is a big problem—it is not something companies do very well.
Is this a problem in the pharma companies you work with? You called their business models broken in our Winter 2009-10 issue (pp.13-14).
This is a problem for all big biosciences companies. It takes good communication and a great deal of trust to allow business-function managers to speak for the company. Large companies have the tendency to put off even thinking of asking these critical questions, because their day-to- day issues eat up all of their available time.
Small companies are different; they are able to articulate their needs and wants relatively easily because there are only a few individuals from whom they have to get consensus; and because every big decision places the company’s future at risk. They have to ask the right questions. That means they take the time to make sure they are doing just that. The problem with these small companies is that they usually have very limited resources (e.g., money).
And you’ve seen this in those bioscience companies?
I have been on the founding teams of 12 bioscience start-ups. It’s critical for a decision-making organization to recognize that it’s no longer a seller of products to its customers but, rather, a bundler of solutions for them.
As one of the chief business officers in these start-ups, my job was to build solutions for our customers; in most cases, these were the big biosciences companies. To be successful, we had to understand their needs and wants, and we found ourselves very perplexed because most of the time these companies really couldn’t articulate what they needed and wanted. That’s why being decision-ready is so important.
What order of magnitude are we talking about?
We probably talked to about 70 of the larger bioscience companies.
So how should organizations be making these critical decisions?
Most companies make decisions in a series of steps that look like those outlined in the diagram below—the more formal the process, the more successful the outcome. The first steps are the collection, filtering, and organization of raw data. A process that we teach in our MBA program for doing this is termed a P.E.S.T. analysis, which stands for Political, Economic, Societal, and Technological. This analysis yields who, what, when, and where.
Next, they convert this information into intelligence, i.e., they deliver these data to specific individuals within the company who put this information into the context of the company’s long– and short–term objectives. We call this the how and why.
This information must then be communicated to other people who have the judgment and responsibility to adopt or modify the new approaches suggested by this new intelligence. Implementation of these decisions is the next step—these decisions must yield some competitive advantages.
What are the difficulties companies encounter doing this?
Companies that formalize these steps and link them with the proper metrics are more successful than those that don’t. But there are two places where they have trouble. The first is aggregating the intelligence in a way that allows managers to make good decisions easily and, importantly, without wasting a lot of time chasing irrelevant information.
The second hurdle is being decision- ready; i.e., able to translate and communicate those decisions into actual processes that people can understand and implement throughout the organization.
As we discussed earlier, organizations need to understand that converting the raw data into useful intelligence depends on asking the right questions. But we find that too often the people taking this step do not have their fingers on the pulse of the organization. That’s partly because they have not been incented properly. From the top down, it is everybody’s job to communicate with customers and understand their needs and wants, and be able to move this information back into the company.
So there needs to be a set of processes in place to allow this information to be disseminated throughout the entire organization. That’s not easy to do in the big company, where too often the people are not incented to think and act in this way. In fact, it’s just the opposite—they’re dis-incented. They’ve been told that this is your job; it’s circumscribed in this particular area; you take this from this person, you add this sort of value to it and you transfer it to this set of individuals; your job is to just do that and not think too much about the overall problems because if you do, our efficiency will go down! Thus, the culture often prevents these skills and behaviors from ever being inculcated in the organization.
The people who make up the company have to move away from being risk- averse to being the opposite—they must embrace change. This means creating a very different culture—a culture of making decisions and of being receptive to change imperatives. It’s that kind of culture that really makes up a decision-ready organization. (See “Don’t Believe All You Hear About Innovation Culture,” CIMS IMR Spring 2011, pp.7-8.)
Tell us about a company that does ask the right questions.
Procter & Gamble is a good example. A few years ago management asked how many of their products were coming from their internal R&D versus from partnerships outside the company.
Then management asked a more specific question: How can we get 50% of our new products over the next five years to come from outside?
That very specific question made P&G reexamine itself. It had to move away from its historical inward focus to the development of processes for interacting with outside organizations. P&G learned on-the-job how to do this, e.g., they had to create a new set of internal resources, including:
-A chief innovation officer.
-Numerous product and project managers.
-Processes for logging ideas onto a “eureka catalog” for general managers, brand managers, and R&D teams.
-Cultivating both internal (plus top 15 suppliers) and open networks for ideas (e.g., Yet2.com, NineSigma, Innocentive and FellowForce).
-Incenting employees to identify outside-generated ideas.
-Re-segmenting its customers and introducing separate business units for big accounts—each with own P&L.
-Partially integrating its value chain with its customers; e.g., linking with Wal-Mart’s databases for category and competitive intelligence.
P&G discovered that for every P&G person who had the skill set to create new products, there were approximately 200 outsiders with the same skills. P&G was successful in addressing their key question. In five years they went from having less than 5% of their products coming from the outside to 37% coming from the outside. Moreover, in the next five years, P&G wants to increase annual sales of products from its outside partners from approximately $1 billion to $3 billion.
Interestingly, P&G concluded that the most difficult part of their process was the creation of a culture of innovation. They estimate that it requires at least seven years to make this change.
And clearing your second hurdle?
That’s where big data analytics comes in. This seems to be the only logical way to convert raw data into actionable intelligence—mostly by separating the relevant from irrelevant information. Big data analytics allow one to do this even when coping with 15 petabytes of data being thrown onto the Internet every single day! (See “Innovation Winners Create ‘Situational Awareness’ with Big Data Analytics Platform,” CIMS IMR Summer 2011, pp. 1-4).
How exactly do you separate the relevant from the irrelevant?
One step is to set up a formal organization in which individuals from various functional areas, and likely from outside, come together to help you ask the right questions. Your experts should focus first on defining your question and, next, on where in those 15 petabytes flying at you every day you should look to find the information to answer that question.
The only way you can even think of organizing all that information is by using tools like the big data analytics. A good example of these tools is our Big Data Analytics Platform (BDAPTM). Remember that every one of the different functions within the company is likely to have a different set of questions. So this is a very big problem, it requires tools (and queries) that are specific to each and every business function.
What actions do you recommend?
One way is to change only one business function at a time. A business function is like a little start-up. You can get all the business managers of that business function into a room at the same time. After they articulate the right questions, they go into tools like big data analytics to pull out the data. Then they make decisions and communicate those decisions to the correct business areas directly.
If there are issues with the culture, then they educate current staff and make sure new hires have the same training. Under these conditions, all employees are focused on customers, i.e., understanding their needs and wants, and working to bundle solutions for them.
This is market pull rather than technology push. You’re reaching out to many different customers and making sure you’re delivering what those customers want. In short, you’re being decision-ready.
As other business functions in your company see the changes being made, they will begin to see the strengths of the process and wish to participate.
Let’s close with your decision-ready reading list.
The text we use in our courses is The Power of Pull, by J. Hagel, J.S. Brown and L. Davidson (Basic Books, 2010). Also helpful is The Thank You Economy, by G. Vanerchuck (HarperCollins, 2011). The IBM survey data cited comes from “Making strategy execution a competitive advantage: Results of research sponsored by IBM and conducted by the Balanced Scorecard Collaborative,” by David P. Norton, at www.ibm.com/cognos.