Capto CEO, Tracy Currie, had the opportunity to sit down with Carol Flagg of RCM Answers during the recent Healthcare Financial Management Association (HFMA) ANI conference. They discussed the business and customer experience opportunities for healthcare in the near future.
Read Carol's article and listen to her conversation with Capto:
HFMA ANI Conference Brings Leaders Together to Discuss Challenges Impacting RCM
Data is exceptionally valuable for companies making decisions concerning reducing costs and increasing revenues. Though it’s seemingly simple to run a data report, getting to the right actionable insight can offer both opportunities and missteps.
See the rest of the article published in ColoradoBiz Magazine.
Today’s demand for big data talent reflects a recurring theme that happens whenever a new valuable technology becomes available. Companies face the conundrum of figuring out how to quickly capitalize on the latest technology to gain business advantage during a time when a limited supply of skilled talent exists in the marketplace.
Internally, the tug of war begins because marketing, operations and customer service all push to leverage these technologies as quickly as possible, while IT tries to figure out how to get it done. The business ends up with two options: develop the expertise internally or partner with an outside resource.
Build the Expertise
The conditioned response is to invest in hiring new talent with the needed expertise or training teams to capitalize on the new technology. We, however, would argue that choosing to develop the technical expertise internally is the wrong approach for most businesses.
Recruiting scarce big data talent is a tall order, and it can cost corporations precious time and hefty compensation packages. McKinsey reports that the United States is facing a shortage of 140,000 to 190,000 people with expertise in analyzing large amounts of data and 1.5 million managers and analysts with the skills to understand and make decisions based on big data analysis.
Recruiting a team for big data is expensive and takes significant time to onboard, train and maximize new capabilities effectively. The team can be invaluable once they are fully engaged and bring a greater return on investment for your company. Unfortunately, far too often, a team member or members can be lured away before delivering the hoped-for value.
Companies often believe they can train in-house teams of employees in new technologies rather than recruiting new employees, but this can come with a significant “cost of discovery.“ Members of the team typically learn by trial and error slowing progress and often causing frustration on several levels of the organization. The company will also invest substantial resources to build up employees’ expertise while losing valuable time.
It could take 12 to 18 months to see tangible business benefits if a company goes down the path of building a new capability internally, whether by recruiting new talent or training a team in-house. By the time the capacity is built and value is gathered from the team, the competitive differentiation is significantly diminished or even lost.
Buy the Capability, But Buy Smart
We encourage companies to consider choosing not to fight the big data talent battle. Companies can leverage the skills, tools and infrastructure of industry leading partners to create an outcome-based relationship, dramatically reducing time to market to capture the sought after competitive advantage. This allows companies to gain a dynamic competitive advantage that returns business results quickly before the advantage disappears.
Business results can typically be realized in less than six months by leveraging a service provider to significantly reduce time to market. However, the key is to buy smart. This means understanding what skillsets you need and at what capacity. You should hire for outcomes versus output—keeping the team focused on the value proposition. It is also critical to clearly understand the ebb and flow of your department and partnering with a team that can quickly flex to meet the demand.
Bottom line: time to market is critical. Waiting for supply and demand to come into balance often means losing sought after competitive advantage. In our experience buying capacity is the better, faster route when you buy smart.
Analytics have become “big” and “intelligent” over the years, but companies still struggle to squeeze the full value of their data analytics to meaningfully direct their go-forward strategies. While we see this trend continuing into 2016, there are some bright spots as technological advances enable companies to wade their way through the murky data lakes toward clearer waters.
Here is what Capto sees on the analytics horizon for 2016:
The herd mentality will remain squarely in place in 2016 because when the latest technologies are “in” companies will invest big. But they will do so in traditional ways, ultimately missing the boat. However, the thought leaders will innovate in new ways to justify the expense and exploit the value of the insights across business disciplines to create a larger return.
Big data is today’s version of the cloud. Because there is a tremendous business opportunity, there will be a lot of investment in this space. Companies such as IBM need to learn how to deliver, value and sell this new business segment. The economic models simply haven’t matured yet. That said, we predict IBM’s Watson and others will be delivering true “insights as a service” in the next few years.
With so many elements of business gaining tremendous value from big data—e.g., marketing, supply chain and customer service—internal competition to own or develop separate analytics capabilities will increase – leading to multiple sources of the “truth.”
With easier, cloud-based tools, businesses can access and analyze data themselves and simply remove IT—which is frequently viewed as the roadblock—from the equation. Until IT figures out how to clearly define its value proposition and more nimbly serve its internal business customers, there will continue to be ongoing frustration with the “IT bottleneck” and other business units will look for ways around it.
With different perspectives and needs, there will be confusion on how to obtain and begin to use the same set of facts. Worse still, the arguments will likely center on which data set is the right one to use instead of how we could use the data we have to move forward. Without like-minded direction on the data strategy, companies will get stuck and not be able to capitalize on the insights due to multiple sources of “truth.”
While there will be major investment, forward movement will be challenging. The companies that move faster will be those that collaborate, avoid silos and approach the insights gained from data as a foundational element to their 2016 strategy.
