Part 3 in our 3-part series on Transformational Analytics
By now you are familiar with our definition of Transformational Analytics:
Business people routinely and easily obtain information that they can customize, which helps them run and continually improve the business.
In the first two parts in this series we drilled down into this definition and developed a framework to make the definition more tangible:
SOGE: Strategy, Operations, Governance, Execution
In our final installment we drill down into the SOGE framework and help you prepare for, and map out, your organization's journey on the road to Transformational Analytics.
Let the journey begin....
"Where are we?"
The first step is a current state assessment of your analytics function.
Ideally, this would be done from an outside-in perspective. A neutral, independent evaluation will provide transparency and thoroughness. Although, with proper planning and execution, some organizations may have the ability to do this "in-house".
Either way, the assessment should:
Have the support of executive leadership - who have agreed to review the findings and recommendations
Be thorough - include all areas of the analytics function, not just the "execution and delivery"
Be transparent - highlight the areas of strength and areas that are lacking. Use this as ammunition for your case to solidify the strengthen the analytics function.
The assessment should include all of the "O", "G", and "E" areas. We will explore these in more detail later in this article.
"Where do we want to go?"
In parallel with the evaluation should be an exercise in clearly defining the business needs.
The scope of this should include all major business functions - sales, marketing, support, finance, product, etc.
It should also examine not just the analytics needs of each organization, but their overall plans, goals, and pain points.
So, while it is important to know that Marketing feels they need a new platform for managing campaigns, what is more important to know is that they have signed up to increase the top of the funnel by 50% next year.
The importance of the "business needs" (as opposed to "analytics needs") cannot be overstated. Quite simply, the purpose of analytics is to make the business successful, not just to provide them with data and insights. If you do not understand what success looks like to them, you will forever be delivering what the business says they WANT, not what they actually NEED.
Remember the Transformational Analytics definition: business users leveraging data to run and improve the business. Not to improve their analytics. To improve their business.
Equally important in the future state vision are the overall business strategy, goals and plans for the company. For example, what is the anticipated growth in revenue and employees in the next 2 to 4 years? It is critical to factor into the strategy the ability for your analytics team, technologies, and process to scale to meet the needs of the business.
Compiling all the above:
take-aways from the current-state analytics assessment
the needs of each business function
the corporate strategy and goals
You will have the raw information for developing the analytics future state vision and strategy.
And thus begins the most crucial, and most delicate, stage in the process.....
Side note before developing your new/updated analytics strategy:
It is easy to let personal experience or bias creep into the future state. For example, perhaps you have implemented MDM at your previous company and think it would be valuable for your current company. But do the business needs truly indicate that it is necessary? Beware: personal bias will tend to skew people to look for (and not surprisingly, find!) affirmation for certain ideas.
There is no "right" or "best" process for developing your new/updated analytics strategy. It is something that has to work for your organization. However, bringing in an outside partner to guide you through the process (not tell you what your strategy should be) is recommended.
Either way - at the end of this process you will need to ensure that you have developed a comprehensive analytics strategy that:
covers the entire spectrum of analytics activities (SOGE): strategy, operations, governance, execution and delivery
is aligned (and agreed upon!) across all the lines of business
clearly articulates the business pain points and how the strategy will address them
describes analytics capabilities (instead of specific technologies / tools)
includes an organizational operating model (high-level roles and responsibilities) - though not necessarily an organizational reporting structure
supports the projected growth of the business for the next two to four years
provides a vision for being a Data Driven organization
As described earlier, the key to delivering an analytics strategy that transforms your business is defining and implementing robust Operations, Governance, and Execution functions.
Let's take a closer look at each of these areas and how to include them in your analytics strategy.
The "O" - Analytics Operations:
As described in Part 2 of our series, Analytics Operations is the glue that holds together all of the analytics activities through integrated processes, workflows, communications, planning, and change management.
Your analytics future state should include a commitment to these elements as well as articulating the business benefits, which typically include:
Clearly defined processes for requesting and granting access to data sets, systems, dashboards
Consistent and efficient communications regarding project requests and status
Timely notifications and updates regarding outages and maintenance activities
Awareness and management of cross-functional analytics projects to drive alignment and understanding of down-stream impacts / required actions
It is likely that the analytics assessment effort has highlighted some of the current analytics operational pain points. The assessment may not directly identify the issues as operational, but when taking the time to investigate the root causes behind them, their operational aspects will be clear. This is especially true for issues related to processes or communications.
The "G" - Data Governance:
The degree, scope, and structure of your data governance will depend on business needs, but at a minimum should include:
Implementation of data trustees and stewards. Identified owners of specific data sets who have the responsibility to authorize access and to monitor data quality and lead any necessary remediation efforts.
Implementation (and maintenance) of a data glossary to properly document the official definitions and calculations for key metrics and KPIs
Implementation (and maintenance) of a data catalog that documents the available data assets: data sets, reports, dashboards, and potentially much more
Processes for reporting, tracking, and resolving data quality issues
Published policies and processes for data privacy and security, as well as any other legal regulations
An audit process for compliance of policies
As stated in our previous article, data governance should not be considered or approached as a hindrance to the business.
Your analytics strategy should highlight a well implemented governance function that enables, empowers, and streamlines the analytics activities.
The "E" - Execution and delivery
All too often, data/analytics strategies focus SOLELY on the technology and capabilities. Or, the strategy becomes an exercise in documenting the Plan - by calling out specific technologies, tools, or products that will be leveraged.
Avoid these pitfalls by focusing on what the technologies, capabilities, and analytics will deliver and accomplish. Don't worry - the Plan and details will come later.
For now - focus on how Execution and Delivery can support the corporate and business functions strategies, plans, and goals.
Some key elements to consider:
Encouraging and developing processes for "proactive technology solutions". The data engineering teams are at the forefront of technologies, and will undoubtedly have valuable input into opportunities to take advantage of these capabilities.
Making a formal position on the elimination and prevention of future data silos
Managing duplicate, redundant, or incompatible tools
Establishing data operations (Data Ops) to drive alignment and streamlined processes for managing data, analyzing it, and producing insights
"How do we get there?"
Your next step on the journey will be to establish a plan that:
Defines priorities / milestones / deliverables
Provides high-level timelines
Identifies an anticipated budget for staffing, tools, and technology
Includes metrics for measuring success
Since analytics is about making the business more successful, your stakeholders need to align, agree with, and ultimately be part of the approval process for the strategy.
Socialize drafts of the strategy to ensure they feel included not just in the input phase, but also the definition phase. Make adjustments as needed, but keep in mind that not every input needs to be or should be incorporated.
This process is critical, but should not be dragged out by an overly consensus-driven approach. This is much easier said than done - and will require navigating the culture of the organization. Again, this process can be aided by a neutral outside party that provides an independent presence.
OK, we have a shared vision and an aligned and approved plan - it must be GO TIME!
Yes, but... only after key components of the Analytics Operations component is in place.
There needs to be a plan (and owner) for handling the communications, stakeholder engagement, and change management components.
The following questions must be answered
Communications
What will be communicated? One set of messages for all, or targeted communications for executives, the analytics community, and the company as a whole?
What format(s) will be leveraged for the communications?
What is the communication cadence?
Program Management / Change Management
How will progress be tracked and communicated?
Progress check-ins will be necessary. What does this look like (who, when)?
As the business climate / priorities change, adjusting the strategy/plan may be necessary. How will this be handled?
Understand what changes are needed. Who is affected? What support is needed to make the changes?
"Are we there yet?"
No.
This journey is a long one - one that will take unexpected turns, encounter hurricane force headwinds, and your destination may look nothing like you envisioned when you took the first step.
And to be brutally honest, it is quite possible that the people who took the first step will not be the same ones who are there to see it through to the end.
Analytics that truly transforms your business is possible. Be prepared for the challenges. Plan thoroughly, but quickly. Execute with energy, passion and fearlessness. Fail early. Regroup and carry on. Don't stop, even after you "get there", because the "there" is is not a fixed or static place.
Share your experiences, trials, tribulations, and success stories with us!
Comments