I recently had the pleasure of being a panelist at Kellstadt Marketing Group’s 2011 symposium: Click: Emerging Media and the Empowered Consumer. My panel covered Business Intelligence, and how managers can get CRM working in their enterprise. One of the questions the audience put forward was about how to start, and what to expect as you start to bring actionable data in.
In our discussion we compared the stages of the enterprise to the evolution of a new country or civilization - where some brave souls have to enter the wild frontier, and establish outposts to grow from. As cities develop and expand, the industry and economy evolve into new and more powerful forms, eventually becoming information-based.
The first stage is The Frontier - a scary wilderness where the enterprise functions without any structured data at all. Some businesses have huge areas of activity that don’t collect or manage any data at all. Up until recently, many consumer packaged goods manufacturers were in this phase. Just like the frontiers of old, this creates vast unknown areas, brimming with opportunity and ready for exploration. And it only takes one brave soul (or a group of them) to get to the next step.
Colonization - the stage where companies start to use data to make suggestions to users, or personalize experiences. Companies in this stage are testing the waters, so just like the first colonies, there are only a few outposts - not a real support network. They are looking to provide a solid case before investing any real infrastructure money. That said, if you’re in this situation, then make sure that your operation is properly set up to prove ROI, because your ’supply ships’ will stop coming if you can’t prove that using data is a winning proposition. Many services companies get caught in this phase, with their management waiting to see proof that it makes sense to invest in anything more than a basic customer database. Once a case is made and accepted by management, then expansion into the next phase is possible.
Industrial Revolution - the stage where things start getting automated at scale. More and more of the company becomes dedicated to getting customer personal and behavioral data pulled into the stream, and infrastructure gets built on a massive scale to expand the reach of data both in the company and out to users. Some banks are good examples of this kind of enterprise - with each product group in the company depending on their customer data to excel, but tending to work in silos, without a centralized view of the customer. Just like in the actual industrial revolution, there are stories of both winners and losers. Some companies will not adjust fast enough. Some areas of the company will hang onto ‘how things were done in the past’. Winners get to move to the next step, which is also a revolution.
Information Revolution - this is where data becomes so central to how the business operates, that the company can say that information drives the business forward. In this economy, if you’re out of the data stream, you’re out of the picture. Due to technology advances in handling large structured and unstructured data sets, massive amounts of internal and external data get joined together to predict behavior, needs and barriers. Models are built to ensure correct customer handling, even with imperfect data, and the enterprise continues to search for what new metadata could be added to make better decisions and offers. Things change quickly in this economy (five years ago who would have predicted that social media would need to be tracked in consumer databases?), and companies like Amazon and Netflix are good examples of leaders that know that continual reinvention and innovation is crucial in order to stay ahead.
With this path to sophistication in mind, we can recommend some steps to get you from where you are to the next level in these Evolutionary Stages:
1. Know where you are. You have to be honest about ‘Where you stand Evolutionarily’. And there are likely to be multiple, conflicting opinions in the company about how data is used. Talk to stakeholders, and avoid proclamations too early in the process. It will take time and persistence to develop a clear picture that everyone can accept.
2. Start at the top. Does your CEO know where the company stands? Does he or she agree that data can help the company evolve? Educate through examples - showing how adding data into company operations can avoid costly mistakes, angry customers, and ineffective campaigns.
3. Make the case to evolve. Investment in infrastructure and process change must be earned. If tests and pilots are not planned to give evidence of ROI, then all the logic in the world won’t convince management to take action on data, so keep the end in mind when agreeing to how experiments will be structured, run, and measured.
4. Think big, but start small. Develop a vision of how your company could be operating if you had perfect knowledge of your consumer, and use this to guide an long-range plan. But since you know you can’t get there overnight, keep the steps in the plan small and manageable. Many successful companies value failures for what you can learn, but it’s also true that a CEO’s favorite ‘learning’ project is small, fails quickly, and delivers information that lasts.
So, are you an Information Revolution company? How are you planning to get there (or stay there)?