Your Data Strategies: #Same or #Goals?

Goldilocks entered the house of the three bears. The first bowl she saw was full of the standard, no-frills porridge. She took a picture with her smart phone and posted it to Instagram, with the caption #same. Then she came to Papa Bear’s bowl. It was filled with organic, locally grown lettuce and kale, locally sourced quinoa, farm-fresh goat cheese and foraged mushrooms. The dressing base was olive oil, pressed and filtered from Tuscan olives. It was presented in a Williams Sonoma bowl on a farm table background. She posted a photo with the caption #goals. By the time Goldilocks went to bed, she had 147 likes. The End. Enter the era of the exceptional, where all that seems to matter is what is new, different and better. When Twitter came out, it didn’t take me long to pick up how to use hashtags. But then hashtags took on a life of their own and spawned a new language of twisted usage. Now we have #same — usually representing what is not exciting, new or distinctive. And we have #goals — something we could aim for (think Beyoncé’s hair or Bradley Cooper’s abs). See also: Data and Analytics in P&C Insurance   Despite their trendy, poppy, teenage feel, #same and #goals are actually excellent portable concepts. When it comes to your IT and data strategies, are they #same or are they #goals? What do your business goals look like? Are you possibly mistaking #same for #goals? Let’s consider our alternatives. Are our strategies aspirational enough? If you are involved in insurance technology — whether that is in infrastructure, core insurance systems, digital, innovation or data and analytics — you are perpetually looking forward. Insurance organizations are grappling daily with their future-focused strategies. One common theme we encounter relates to goals and strategies. Many organizations think they are moving forward, but they may just be doing the work that needs to be done to remain operational. #Same. When thinking through the portfolio of projects and looking at the overall strategy, it is common to wonder, “Isn’t this just another version of what we did three months ago, even three years ago?” Is the organization looking at business, markets, products and channels and asking, “Are we ready to make a difference in this market?” No one wants the bowl of lukewarm, plain porridge — especially customers. Are we aiming one bowl too far? On the flip side, our goals do need to remain rooted in reality. It’s almost as common for optimistic teams to look at a really great strategy employed by Amazon, only to be reminded that the company isn’t Amazon and doesn’t need to be Amazon. It just needs to consider using Amazon-like capabilities that can enable the insurance strategy. Data lakes can be a compelling component in modern insurance business processing architectures. But setting a goal to launch a 250-node cloud-based Hadoop cluster and declaring you’ll be entirely out of the business of running your own servers is not a strategy that’s right for everyone. If the organization is pushed too far on risk or on reality, it creates organizational dissonance. It’s tough to recover from that. Leaders and teams may pull back and hesitate to try again. Our #goals shouldn’t become a #fail. Finding the “just right” bowl. Effective strategies are certainly based in reality, but do they stretch the organization to consider the future and how the strategies will help it to grow? When the balance is reached and the “just right” bowl full of aspirations is chosen, there is no better feeling. Our experience is that well-aligned organizational objectives married to positive stretch goals infuse insurers with energy. This example of bowls, goals, balance and alignment is especially apropos to data and analytics organization. It is easy for data teams to lay new visuals on last year’s reports and spin through cycles improving processing throughput. To avoid the #same tag, these teams also need to evaluate all the emerging sources for third-party aggregated data and big data scalable technologies. With one foot in reality and one stretching toward new questions and new solutions, data analysts will remain engaged in providing ever-improving value. See also: How to Capture Data Using Social Media   Even if an organization could be technically advanced and organizationally perfect, it would still want to reach for something new, because change is constant. Reaching unleashes the power of your teams. Reaching challenges individuals to think at the top of their capacity and to tap into their creative sides. The excitement and motivation that improves productivity will also foster a culture of excellence and pride. We are then left to the analysis of our individual circumstances. If you could snap a photo of your organization’s three-year plans, would you caption it #same or #goals? Inventing your own scale of aspiration, how many of your goals will stretch the organization and how many will just keep the lights on?