Turning the Data to Insights to Action Mantra on its Head for Better Business Decisions

Transcription

1 Turning the Data to Insights to Action Mantra on its Head for Better Business Decisions There are lots of situations where we start with a hypothesis, get some data, put it through some black box logic, get some insights and take some action based on the analysis. It works well until it doesn t, typically when you need it most. You know the signs. There s a big decision at stake - - something that defies routine analysis. The decision maker and the analyst are each holding their breath. The decision maker has given the best direction s/he can. The analyst is doing the best s/he can. The deadline approaches. But both sense that there s going to be a shortfall on guidance for making the big decision. If we re honest, most of us have faced situations where the standard data to insights to action approach seems to be forced or somehow not up to the task at hand. What can be done? First, call it for what it is. I m a strategist who uses data analytics in many situations. If I m not getting the quality of insight that I think I can get, I ll work the analytics harder or define the hypothesis more clearly. But sometimes that s not enough. Driving harder on the same roadway won t get you there. Suiting up for a different route makes more sense. A client, the divisional president in a large company, was sweating with this very challenge. He and his leadership team needed to decide on a response to a competitor who was likely to bring a comparable product to market at a price that was 30% or more below the price of their most important brand. He and his people had done good analyses of price elasticities, customer preferences and more. This yielded some valuable learning about their options. But nine months later, the leadership team was not comfortable about committing to an option. Their data analysis and insights didn t add up to action. While the temptation was to double-down on more analysis, we asked them to turn the process on its head. We started with the action (outcome) and carefully worked our way backward to insight, data and better action. The goal was to see around the curves in the road better and get to the best decision faster.

2 Here s what you can do if you find the data to insight to action pathway slow moving or frustrating in another way. The approach has 4 steps: Actions Revealed; Insights Unearthed; Analysis on Must Haves Done; and, Final Actions Ready to Go. Actions Revealed Start by getting the hard issues up front. What are the final actions (outcomes) that make the most sense based on what we know now? In the price competition example, 5 final actions were winnowed down to Beat em or Join em. The first involved making additional investments behind the existing brand. The second involved developing a product that could be priced competitively against the lower priced competitor. Further on in the process, after you get more insight, another option may seem like it makes better sense. That s fine. You ll probably get to that realization more reliably by this approach then by applying black box logic to identify the most viable outcomes. For now, choose two or three substantially different (mutually exclusive) outcomes based on your experience and existing analysis. This can be done very quickly depending on the challenge in getting the views of various stakeholders. It s important that stakeholders see these outcomes as viable, even if an outcome is included that they don t prefer. It s not important that all stakeholders support each outcome. People will have their favorite(s). They just have to agree that they re viable in the context of the business situation at hand. Insights Unearthed When you have a couple of outcomes, some conditions for success, some criteria for the decision, and some boundaries for what is and is not fair game for the discussion, you re ready to get the stakeholders together and deconstruct the outcomes. Include decision makers, analysts and functional contributors who have a stake in the outcomes that you ve identified. It s particularly important to have the key analysts participate. This way everybody has a chance to see what s most useful to analyze. And, how possible limitations in an analysis may impact how it s best to proceed. Too often, we ve seen decision makers get blind-sided by well-intentioned, well-prepared analyses that are off the mark for the decision that needs to be made.

3 And, one of the key problems that analysts have is not seeing enough of the picture early enough or continuously. So, they have to depend on a translation of what others believe is the end game and where analysis will do the most good. For each of the outcomes, figure out what you would reasonably have to believe for it to be successful. Don t rationalize or over think it. So, for our Beat em or Join em outcomes, we d have to have certain conditions in place in technology, investment, manufacturing, marketing, sales, regulatory and other areas. For example, in the Beat em outcome, you d have to believe that you could afford to spend enough behind your existing brand to minimize the price advantage of the competitor in key market segments or put up other barriers for the competitor to scale. Preparatory discussions will surface a number of guiding principles that suggest what probably will and won t work to achieve the outcomes. For each of the conditions, figure out what s important to know, and how accurately you need to know it. This is where you think some more about the data collection and analysis implications. But, hold off on actually doing the analytic work. What makes the most sense to analyze may change based on your overall consideration of the outcomes and which one(s) you choose to do more work on. This is different than the traditional approach where you re working forward from analysis to identification of options. Here, you re working backward and deconstructing each option in a disciplined way to find out what you d have to believe for it to reasonably succeed. When done well, this will yield important insights. If it s not reasonable to believe that what s required for success will be there, it gives you a major cause to consider that outcome as non-viable or less preferred. Classic route Re-routed Data Choice Action 1 Action 2 Logic Logic Deconstruct Deconstruct Choice Action 1 Action 2 Data Establish criteria for choosing between the outcomes that you identified. So, in the price competition example, we used revenue, profit, market share, feasibility, and degree of disruption in the existing business. Estimates by stakeholders are fine at this point.

4 Also, be clear about what s on the table and not on the table for the discussion. In the price competition example, there was no appetite for buying a company that specialized in manufacturing lower-priced products or in investing a lot more money than already had been budgeted. This set some fair game boundaries, at least until a rationale could be provided to remove these limitations. Analysis on Must Haves Done As the process moved ahead, it became clear to our client that sales distribution partners and strong focus on 2 market segments were the keys to success. These were must haves. These keys were not readily visible before, especially in combination with each other. The analytic focus shifted to these critical higher risk, higher return areas. Armed with a clear understanding of what needed to be done and why it was important, the analysts produced the additional guidance that the decision makers needed to move ahead. Other analytic tasks that seemed important previously were stopped. The analysts still needed to iterate through their analyses, but the focus was sharper and confirmed by the stakeholder group. Final Actions Ready to Go If done effectively, it s possible to get agreement very quickly on which outcome makes the best sense or if an outcome different than the ones already considered should be looked at, and what additional information is needed to make a sound decision. In the price competition example, the non-traditional approach helped to clarify the outcome that made the most sense - - using the existing brand and leveraging the distribution channel to fight the lower-priced competitor. The preferred outcome was different from the ones stipulated at the start. Before approaching the challenge this way, the prevailing opinion was to back a different option and do further analysis in areas that were not as crucial to the best decision. Why the approach works A smart and accomplished management team had been debating the best decision for almost a year. Within a month, they were able to make a decision about the option they wanted to pursue, get broad commitment from the stakeholders, focus the analysis in a way that was not possible before, and take initial steps to put the decision into action. Why did this approach work? 4 main reasons. 1) This approach is aligned with the proverb You don t know where you re going, unless you know where you ve been. By stipulating outcomes upfront, even if the final outcome is different, the team was able to use the exploration, in a manner of speaking, to see where they ve been. The simulation made the unfamiliar more familiar. By asking what they d have to believe for an outcome to be successful, they were able to get the hard issues on the table instead of overburdening the analysis with secondary and smokescreen issues.

5 2) An important social dynamic is at play in this approach. Stakeholders are more willing and able to put their favorite solution on hold and suspend ego for a while, so that everybody s judgement and creativity can be brought to the table. At least, they can agree to suspend judgement temporarily, while this approach works its way through. Why? Because, the rules of the game when played this way say that each outcomes is to be adopted by the group and evaluated as if it s the chosen option. So, it s safer for people to explore options they otherwise dislike. You can hear people thinking to themselves, heh, I ll play they already know that s not my preferred route. Can powerful or opinionated people cheat and bully their way forward. Sure. But there are several opportunities to call them on it. Remember, the decisions that get made using this approach are usually tougher ones. The management teams have spent lots of time grappling with them and don t feel as confident as they d like in proceeding with one. 3) You might be thinking doesn t this approach limit free wheeling creativity and innovation? Our experience shows us the opposite. Although, it wasn t developed to help cultivate innovation, it actually provides a structure within which to channel it. Creativity is more likely to be applied at points of maximum leverage. We find that participants are more generous with their ideas. 4) Have you experienced the situation where projections about things like sales get more optimistic the longer you project into the future? This approach tends to keep that tendency in check. By working backwards and looking critically at what you d need to succeed, we ve found there s less likelihood to make the numbers look rosier in the out years. While this approach is very accessible, it does require a different way of thinking. It can be used with all types of decisions, and is particularly helpful with certain ones. The decisions typically involve higher stakes, non-routine considerations, different groups of stakeholders and significant data analysis. The example used above focused on product strategy. Other applications might involve situations such as agreeing on product development roadmaps with important customers, deciding on the best changes in a product portfolio, improving the competitive positioning of an organization or taking a unique view of decisions that have become routine and lost some of their competitive edge. I want to recognize my colleague Mark Hurwich, a very talented facilitator of effective decision-making, who helped to pioneer this approach. Are you grappling with a high stakes business decision? Are you worried that the traditional bottom up data to insight to action path might not get you where you need to be well enough or fast enough? Do you want to make all the effort you put into analysis yield more? I d like to hear about it and share ideas. Please contact me at , jfischer@calibreconsulting.com. Illustrations: Mark Monlux Calibre Consulting Group helps organizations glean insight from market and customer data that directly increases ROI.