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Oct 4

Start At The Very Beginning

start_feet It’s “People, People, People” that make the difference when it comes to getting the most from your data, but how do they get started? With the right approach, leveraging data will help an organization be better, faster and more efficient at every facet of meeting the needs of their always connected and in control customers. With the wrong approach though, attempts to leverage data can result in confusion, missteps and wasted dollars. What needs to happen to get started on the first path and not the second? Rodgers and Hammerstein had it right, “the beginning is a very good place to start”.  Start there and build a strong foundation. Establish objectives that align with the business. Have a vision for the future but optimize what you have first. Don’t attempt to jump too far at one time and recognize it is a journey where value compounds. It takes new thinking and new behaviors across the organization to capture and unleash the power of data and a complete understanding of data, its potential as well as its limitations. Following are some considerations I hope you will find of use as you build your data strategy.

Data Is A Piece To A Puzzle, It Isn’t The Puzzle.
Data is a piece of understanding the customer journey, the market opportunity and optimization opportunities. To get the clearest view though, multiple data points should be placed in context and integrated with other puzzle pieces such as research, understanding of motivations and behaviors, market data and other business factors. Whether there are a few data points or many, rely on people (and give them enough bandwidth) to interpret, analyze, contemplate, draw conclusions, generate ideas and decide actions.

What People See Is All There Is (to paraphrase Daniel Kahneman).
Be careful because our vision is clouded by hidden biases and barriers. In other words, we see what we expect to see, want to see, are limited to seeing, have time to see and are rewarded to see. To limit negative impact, have the right expectations, the right people (and enough of them) and design rewards and incentives to motivate curiosity and seeking an ever more crystalizing view of your customer, market, business and future.

Yes, But Does It Matter?
Just because you have the data does not make it meaningful, useful or actionable. Using too much data or not enough in your decision-making can lead to wrong conclusions that then lead to wasted efforts and resources. Set up filters that keep efforts focused and prioritized but not so much that you miss underlying causes, signals and trends.

Courageous People Still Required.
The variables and influencers that go into almost every business are such that there is not an absolute truth to be achieved or a perfect prediction to be made. Data, regardless of size, is not a crystal ball. No matter how robust the analytics, past performance cannot precisely account for shifting market preferences, irrationality of human behavior, the results of untested initiatives or new types of competition. No amount of market research will get your customers to accurately tell you why they do what they do or what they will want in the future. They simply do not know. To stay in front of the market, today’s world requires vision and bold actions. Data will inform these, but cannot tell you what it has no way of knowing.

And You Will Trip.
At least it will feel like you did. Some of what you try will not work. Some of what you thought was causation will turn out to be correlation. You will design reports that don’t tell you what you need to know. Solutions you thought were perfectly aligned with customer needs, will not be. You will miss some important signals that will then look obvious with hindsight. Each step though will teach you something and will help you journey closer to the truth and to better products, better communications, better customer experiences, more efficient operations and inspired innovation.

New Technologies + Old Ways Of Doing Things = Disappointment.
To get the most out of your data, the organization must be collaborative, engaging and foster risk-taking and exploration. It must handle change, development and innovation in new, iterative and agile ways. An active thinking mindset heavy on logic, reasoning and comfortable with complex decision-making is necessary for positions across the organization. Marketing and IT must together forge a new way of doing business and the entire organization must work to ensure the right philosophies, people, training, structure and incentives are in place to support this new way of staying in front of the needs of the market.

Right People, Right Need, Right Focus.
There are many facets associated to working with data including compiling, integrating, managing, mining, reporting and analyzing. And another set of functions associated to turning insights derived from the data into new capabilities and actions. A mix of skill sets and competencies are required to keep eyeballs on interpreting and leveraging data for the needs of today while concurrently having enough doing the same to envision and prepare for the needs of tomorrow.

Generate Meaningful Customer Value With Care.
The always connected customer is expecting you to leverage data and technology to stop pushing irrelevant messages and let them start pulling what they need when they need it. This requires judgment, creativity and commitment to the long term value. In fact, data does not remove the need for creativity, its importance is increased. The better targeting and potential for improved reach that data and technology affords is of little value if the messaging and content is not engaging, compelling and relevant.

Don’t Go Chasing Everything.
According to Forrester Research, on average, organizations are using just 12% of the data they already have. This is as true for marketing tactics as it is for data. Before chasing new, first focus on optimizing what you have. When acquiring new, the latest, most popular software solution or marketing tactic may not be the right solution for your needs. Carefully align business objectives and priorities, built from business and customer insight, with solutions. Take on new only as quick as your team/department/organization can handle them. Focus on a few new and do them well. Consider three longer term priorities that require stepped development concurrent with a continuously rotating set of three shorter term priorities that you can develop in a quick, iterative and agile way.

While Your Action Figure May Not Make Sense, Make It Interesting.
Show and tell is as important now as it was in Kindergarten. An action figure is no longer what you share, but you must find other ways to engage your audience. What the data means, what actions the outcomes should inspire and the results of actions already taken may seem obvious and compelling to you, but they are not to anyone else. Spend more time sharing your learning and enrolling the organization in the inspirations, implications, results and action steps than you are spending acquiring it. Celebrate little victories and as much as possible turn data into stories with pictures.

Take It Very Seriously.
A final consideration is to be thorough when defining your data management, governance and compliance plans, including how the organization is approaching security, privacy and access.

The right approach to data is the foundation for ever improving insights, optimized resources and engaging customer experiences. I’ve shared some of the considerations I find important when working with data. I hope there was something in there that helps you with your planning. It may all seem overwhelming, but just as Rodgers & Hammerstein advised, “start at the very beginning”. As with Do Re Mi, with the strong foundation of notes, a beautiful song can be created. For your data strategy, with a strong foundation of the right behaviors, expectations and resources, the significant benefits of data will begin to be realized.

One Comment
  • […] And what data can and cannot do. Don’t expect too much or too little. Being data-driven does not mean that every decision is or should be data dependent. And too much can be a bad thing. More is certainly not better, especially if it means confusion and misreads. Successfully being data-driven is less about the amount of data and far more dependent upon how the data is accessed, interpreted and applied (and how it is not). There are a number of cautions and considerations when working with data outlined in this recent post. […]

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