Over the past few years, I have spoken with executives from over 20 health plans. I often end up hearing about the data and analytics challenges they face. In the broader market, people like to talk about the next shiny object, the new technology that will drive disruption, and so on. But in reality, I found most large healthcare companies are plagued by serious core issues that hold them back (I’ll use my health plan experiences to illustrate what is a much broader issue industry-wide).

It is made doubly worse by what I call the twin explosion problem: the explosion of data and the explosion of market demands. Between those two things lie everything else that gets strained to and often past the breaking point. Toss in security concerns and migration to the cloud, and we have an industry that I think at times is moving backwards. The following is a summary of the issues I heard in my conversations.

The explosion of data

Everyone knows now the story of how much data we are creating today vs the rest of human history combined. The more data increases, the harder it gets to distinguish the signal from the noise. The more data we see, the more paralysis we have. When we lose confidence, we hesitate to take action. Or we act on misinformation and cause harm. The following represent a few ways the growing volume and velocity of data is creating challenges:

  • Hard-to-use legacy data – Historical data allows us to create a picture of who we once were. It is the ability to look in the rear-view mirror and see what happened. But the problem is that a lot of historical data sits in legacy systems that were designed to store data, not use data. And it often means the data is fragmented, poorly defined, incomplete, inaccurate, and so on. Many large healthcare companies have grown through acquisitions and inherited old systems, or simply never bothered to modernize. This is an issue when they are also trying to leap into the future by bringing in all kinds of new data. In the context of legacy data systems, a jump to the cloud can sound scary.
  • Slow data is old data – One of the most interesting features of data today is the short latency between when an interaction occurs and when that data can be shared. That latency is going to near-zero. When time latency goes to near-zero, the impact is not linear, it’s usually transformative. And so we end up talking about real-time applications that were unimaginable before. Want to do just-in-time analytics at the point of interaction? That’s possible now. But the problem is that most data processes for large healthcare companies are run in batch processing mode. The modern distributed, fast way of real-time computing is a challenge, to say the least.
  • Integration struggles – Putting all the data together into one environment and making it accessible by the business has been a significant issue, and that’s just talking about the data they use today. What will happen when internet of things, social, mobile, and other streaming sources of data start flooding the data lake? And what happens when we re-purpose data (which, by the way, we always do – think medical claims were designed to capture gaps in care? Think social media data were designed to detect depression?). When we re-purpose data, the old data standards, structures, and quality go out the window – what do we replace it with? And how do we determine if the data is any good in the new frame of reference?
  • Missing the big picture – Putting data together into a meaningful and coherent picture of a person or provider or other participant in the system is the ability to see the forest instead of the trees. This requires knowing what a holistic picture looks like, and that means having a semantic model of who a person is, or provider, or employer. This is about using bits and pieces of data to create meaningful and relevant representations of the real world. Think that’s easy? Just ask Google how much computing power they use to do it. That’s much harder than just building data or analytical models, which is where most people live.

The explosion of market demands

The convergence of trends hitting the healthcare industry is creating an environment ripe for change. I have heard about the need to push towards real-time solutions, to incorporate broader determinants of health, to make care more consumer-centric and so on. From consumerism, behavioral health, value based care, social determinants to AI, machine learning, digital health, and telemedicine, markets are demanding answers on many fronts, simultaneously.

  • Expression of need gap – Many market-facing business executives do not understand data and analytics. The most common complaint I heard from internal staff is that the market executives don’t know what they want and would often fail to recognize a good solution. I believe this is true. I also believe the root-cause of this runs very deep and has to do with long-standing culture. In particular, this fact tells me most companies are not analytical competitors (in the Davenport and Harris sense of the phrase). That’s a serious issue and probably needs to be fixed fast.
  • Work order friction – It takes time to make a valid request and have it understood and queued. What I often hear from business executives is the need for them to have market-ready solutions that can deep-dive into areas their clients want to dig into fast. Instead, doing that requires going through the friction of creating a work order that only serves to frustrate the business executive who wants or needs development support now. Instead of focusing on results, business executives are chasing down IT, data, analytics, informatics or development operations staff to find resources.
  • Request backlog – There is an ever-growing backlog of work orders. Imagine how hard it is to support all the needs of the business when IT, data, analytics and informatics staff are dealing with all the issues listed above. Staff are usually running at full throttle and still not keeping up. Do that over an extended period of time and the chronic stress creates blinders on creativity. Teams learn to survive by focusing on short-term hacks. If I considered work product as assets, I would be constantly writing them off as losses the next year. If you want to quickly know how inadequate a data and analytics strategy is, just look at the size of the work order backlog lined up against the satisfaction level of business users. It’s usually frightening.
  • Governance headaches – Each of the many sources of data has a specific origin and therefore specific governance, security, and access rules. This means keeping who can see what straight is a big headache. Said another way, legitimate concerns about who gets access to data and who has rights of use limit the ability for a company to build support for innovative business use cases. For the sake of safety and governance, healthcare companies often broadly restrict access, limiting data productivity and innovation. Moreover, the application of data (for example, EHR) to care for people in modern ways was often not imagined when the data were created (many EHRs are still glorified digital filing cabinets with crude workflow tools).

Caught between a rock and a hard place

If ever there was an appropriate saying for this situation, this is it. Large healthcare companies really are caught between a rock and a hard place. Data slamming them from one end. Market demands slamming them from the other. Getting out of this jam is not going to be quick and easy.

Healthcare companies need to deploy an end-to-end strategy and framework for how they will turn their data into a strategic asset and competitive advantage . They need to be able to explain how they can go from data to market demand, and how they can go from market demand to data in a cost-effective and cost-efficient way. Or in more modern terms, in a more frictionless way. And they need to do this while also imagining the company they want to be, not the company they’ve been for the past 10 years.

Every at-scale healthcare company I have ever seen is silo’ed. Without executive support and alignment throughout a company’s internal and external functions/departments, they will continue to be plagued by these issues. That’s a shame, because they may just miss out on all the powerful technologies that are converging on the industry right now and open themselves up to disruption.