Our thoughts on the future of business
How can you innovate when your strategic decision making is stuck in the 1980s?
Jonathan | June 11, 2018
Rapid innovation is quickly becoming a necessary capability for survival across most industries. In many companies, strategic decision-making is a bottleneck that inadvertently throttles this innovation. Organizations can dramatically improve both the speed and outcomes of their strategic decisions through a combination of data science and machine learning, tools, and process changes. This post describes the changes required for breakthrough strategic decision processes, and how SnapStrat can provide technology to empower decision-makers.
According to a CB Insights survey of ~700 enterprise strategy executives, 83% of respondents believe their company has at least moderate risk of disruption by emerging technologies and companies. Despite this, these same executives also reported that 78% of their innovation portfolios were focused on incremental improvements rather than addressing disruptive risks.
Why? As I observed in my 25 years as a strategy consultant, the most common response to that question is the ubiquitous, “we’ve just always done it that way.” In 2018, that answer no longer works; there are better, more modern approaches. Strategic decisions can be digitized just like other elements of the enterprise, but executives first need to acknowledge they can and must change.
We will first address what breakthrough strategic decision-making looks like, then talk about how SnapStrat enables companies to cross the chasm to achieve those breakthrough outcomes. SnapStrat addresses a broad range of strategic decisions ranging from marketing spend allocation to strategic portfolio optimization. For simplicity, we will focus here on strategic portfolio optimization, that is how an organization spends its discretionary capital and resources on projects.
The 4 key elements required to cross the chasm to breakthrough decisions
1) From Subjective to Data-driven
The classic annual strategic planning process often has two issues: 1) It’s annual, 2) it’s not strategic.
As Peter Drucker famously said: “If you can’t measure it, you can’t improve it.” Almost every executive would acknowledge the truth of this statement, so why do we so rarely measure our strategic decisions? No one questions the value at stake for these decisions, but most organizations make them in a conference room following a series of slide-based proposals with limited data that often can’t be easily compared across projects. Frequently, traditional biases are introduced that limit the ability to innovate, such as:
- Allocating the ‘pie’ based on last year’s number and function size
- Financial impact gets top priority (even if it doesn’t fit stated strategies)
- Allowing a single stakeholder to make all of the decisions
- Avoiding any risky projects
Breakthrough strategic decisions must be based on comparable business case data across all projects. It is also important that resources as well as costs are allocated (at least at an aggregate level) to ensure that the organization can actually execute on the selected portfolio of projects. The data used to compare should be predictive, not just backwards-facing. The ability to build predictive analytics on nearly any data set is dramatically improving the access to this capability.
2) From One-dimensional to Multi-dimensional
Of course, simply using data to make decisions isn’t enough, you must be able to appropriately evaluate the data. One of the primary reasons that strategic decision-making is so difficult to change is that these decisions are multi-stakeholder, and each stakeholder is evaluating the decision based on different criteria.
For example, Marketing may care most about brand equity or market share, Sales about revenue, Finance about EBITDA, Product about new product introductions, etc. The reality is that many organizations end up simplifying their decisions to a single criterion, often ROI. Of course, a balanced scorecard isn’t new, but how many organizations have implemented it in a data driven way that impacts a diverse set of decisions?
Breakthrough strategic decisions must be weighed across multiple criteria in a way that not only balances conflicting objectives, but also ensures that the process is transparent and all stakeholders have a voice.
3) From Ad-hoc to Repeatable
Organizations have spent countless amounts of capital automating business processes—first back-office, then customer-facing processes, but almost none on strategic processes. Typically, the strategic planning process is run in meetings with slides, spreadsheets, and perhaps consulting. In a world where business cycles were long, and strategy was mostly static, this worked well. That world no longer exists.
Breakthrough strategic decisions require the same degree of consistency and automation as transactional processes. These processes need to be repeatable, documented, and with clear objectives and decision rights. A clear process will magnify work of business analysts and consultants and ensure that their work is leveraged effectively and consistently over time.
4) From Static to Learning
Innovative businesses must be agile, and agility in decision-making requires that we understand and learn from each decision. Historically, these feedback loops have been weak in most organizations, largely because there was no repeatable process in place.
But the emergence of machine learning technology dramatically changes the importance of learning loops in decision-making. In our strategic planning example: how much better-off is a company that can accurately predict the likely outcome of a project? The chasm for companies that do not invest in ML technology to develop and improve predictive models is growing wider by the day.
Machine learning reinforces the correlations between specific data elements and decision criteria. Measuring the strength of these correlations can constantly improve the accuracy of the predictive analytics we mentioned in step #1. Machine learning can also be used to detect changes in business context and adapt predictive models automatically.
The SnapStrat Solution
SnapStrat was founded on the premise that proven data science and machine learning technology can be used to enable executives to cross the chasm to breakthrough strategic decision-making.
SnapStrat incorporates several features that enable this breakthrough:
1) SnapStrat uses your data to provide prescriptive analytics relevant to your specific decision
SnapStrat uses your existing data to improve your strategic decisions. We build predictive models around your data that correlate to the specific criteria you wish to use in making the decision. Our optimization technology takes the prediction and produces a solution that allows you to closely tie strategy and execution.
But our commitment goes beyond our software. We our committed to improving the outcomes of your most important decisions. That commitment comes with years of strategy experience, and a singular focus on ensuring that the SnapStrat tool is directed at exactly the right factors that will generate the best outcome for your business.
2) SnapStrat allows you to run multiple “what-if” scenarios reflecting different stakeholder priorities
It is hard to make decisions across functional silos because there is no common view of decision criteria and data. SnapStrat lets you run multiple scenarios with differing levels of importance to criteria, allowing all stakeholders to have a complete picture of the trade-offs between scenarios. The common view of data that SnapStrat provides enables transparency across stakeholder groups – everyone may not agree with a decision, but everyone will understand why a decision was made.
SnapStrat also allows our customers to specify any number of constraints to a decision (examples: at least x% of our portfolio in innovation projects, no more than y% of a specific function’s resources can come from outside vendors, etc.). This constraint handling means that the outcome of a decision is one that works for your company, not a theoretical science project that could never be implemented.
3) SnapStrat enables an agile and repeatable workflow that aligns strategic decisions to execution
Rather than forcing our customers to change their workflow, SnapStrat’s highly configurable platform tailors to existing workflows and integrates with your downstream systems. SnapStrat’s configurability also means that you can adapt and improve your workflow, data sources, decision criteria, and constraints. We start each implementation with a design workshop to ensure that our platform is configured in the right way to support your decision from the start.
4) The SnapStrat tool learns and improves over time and evolves as your decisions and your business changes
In today’s world, business context changes continuously. How can you expect your Power Point decks or Excel models alone to drive a strategic planning process that enables innovation? SnapStrat not only learns from changing business context, but it automatically adapts to it by adjusting its predictive and optimization models to reflect the current business reality. This closed loop machine learning process also allows your decisions to improve over time as more data becomes available.
Strategic decisions are hard. Too often they fail to achieve the desired value, but this doesn’t have to be the case. By implementing a data-driven decision model, you can start the journey towards breakthrough strategic decision-making, and become the hero of your business.
We are SnapStrat. Founded by a team of strategists, business operators and technologists, we would love to help you transform your most important strategic decisions. Please contact us so that we can talk about how it might apply in your business to you.