The Big Data Transformation – Step 1: Awareness
This article performs a critical review of the current usage of the information in –unfortunately- many big corporations. The Robin Sharma equation states that better awareness leads to better choices, which leads to better results. This article is all about awareness… And the fact that your organization owns a troupe of data analysts or even a whole business intelligence department sometimes prevents you from doing this awareness check and monitoring to which extent your business is truly data-driven and you are exploiting all the information assets you have.
Data: my precious!
Traditionally, both data and analytical capabilities have been “owned” by a particular department (call it Business Intelligence or BI if you want). All other departments have been turned into demand units. This set-up worked well for a while, but as the interest in the data increased, the demand grew up as well and the supply department couldn’t handle the amount of requests coming from everywhere in the organization. The result was in many cases the creation of a prioritization process the demand units had to adhere to. Obviously, prioritizing across demand units was challenging and very often with an unpredictable political dimension (“why is a request coming from sales more important than one made by customer care?”), which led to the allocation of a certain amount of man days per demand unit. This “solution” presented 4 devastating consequences for implementing a data-driven performance-oriented organization:
- The supply unit, who actually owns the key to unlock the transformation, gets more and more comfortable in this set up: in order to obtain access to the data and reports, the demand units “buy” the supply unit more resources to get the job done, obviously outside the prioritization process. Those who could (and should) drive the change are not interested in changing anything as they are in a privilege and power position.
- The time-to-information drastically increases: going through a process where every single request needs to be clearly formulated, reviewed, be given an effort estimate in man days, get prioritized with other requests, etc.
- The organization focuses on reports and not on analysis: the man-days in – reports out paradigm doesn’t leave room to the analysis of the outcome. The demand unit requests a report of something instead of working together with the supply unit to understand how the available data and the proper techniques can support a business decision.
- The data department becomes reactive where proactivity is required and proactive but in a “disconnected” way: the supply unit works in 2 modi: creating and delivering the reports the demand units request –with no further questions asked or answered- and taking time to come up with its own proactive analysis but lacking the business context and guidance. The gap between the actual business requirements and value inferred from the data increases
In-unit capabilities: the wrong skills and wrong focus
The demand units end up reckoning that a data-driven approach is a must to drive the business. The business is about KPI’s definition and monitoring and the idea of “what can be measured can be improved” is more and more present in the leadership’s mindset.
The response to this increasing data exploitation need is the creation of local in-unit teams with data and analytical skills, pursuing 2 goals:
- Bridging the gap between data exploitation practice and the requirements of the business: a team of people with more understanding of the business goals and pain points able to find answers and guidance in the data
- Skipping the centralized process: everything the local team can do by itself doesn’t have to go through the prioritization process
Even if the idea is per se appropriate, it quite often ends up in a rather less promising implementation: instead of focusing on understanding the insights available in the data, the local team looks after the KPI monitoring and reduces its responsibility and field of action to create KPI reports for the demand unit management. The dependency on the central supply unit remains, as the information systems are provided by them, who react reluctantly to give access to “external” units instead of creating reports for.
Me Tarzan, you data
One additional problem of the local data and analytics teams in the demand units is the data employees’ lack of skills, highly motivated by the management’s lack of understanding about what a data driven organization is.
The mere monitoring of KPI’s does NOT required any particular skill related to understanding the data, intelligence inference, trend analysis, etc… It’s just a mechanical exercise of transferring data from a system to another one, formatting the output in MS-Excel and creating a fancy corporate branded power point.
The wrong set of skills is a consequence of the “lack of competence” of the management in terms of understanding how exploiting the data is a must to boost the business performance. If you ask any department in almost any organization if they are “data-driven” they will say “yes”… and if you ask them to prove it, they will show you their latest performance report. That’s the issue: the management of the different demand units (sales, marketing, customer care, human resources, partner management, etc) don’t know what data-driven means, and this is not a reproach to them (“How could the CMO know that analyzing the correlation between weather and out-door advertising campaigns of the competitors might have an impact on the opening rate of the last newsletters direct marketing campaign?”)… For me and paradoxically, this evangelization exercise is to come from the BI department –but of course, it means they need to be closer to the business (“How could they know that marketing is running a newsletter campaign?”)
Social media: play it right or stay away
Social media is (surprisingly) quite new for many companies… And the fit into their organizations is an uncomfortable challenge. Is it a sales topic -social commerce-? A brand topic -brand perception, reach, etc-? A pure marketing topic -vehicle of viral campaigns,etc-? A customer care topic -Twitter as the complaint channel per excellence-? or should it be driven out of the Corporate Communication department –one voice over all channels-? Actually, if it can be all those, isn’t it important enough to be an unit on its own?
These difficult questions usually result into a bad solution for everybody. Quite often you fin it split cross-over departments, leading to a constant internal fight and communication overhead where everybody does his piece, or even worst, to a fragmented and sometimes contradictory message to the customers.
Instead of “squeezing” the social media channel to get feedback “for free” from your customers and prospects, to run controlled tests for new products, campaigns, new products, etc. the fragmentation and the lack of skills everywhere leaves the underlying information in social media streams sadly unexploited.
You are not alone in the market
With all the internal issues, nobody has the time to look beyond the department borders. The marketing and sales actions are just not in sync with the competitors’ campaigns, new offerings or feedback given from their customers
The social media real time feed pinpointing the weak spots of your competitors is just ignored. Without an almost real time early warning system to monitor new entrants and adoption of substitute products (in Porter’s language), a reaction to a prompt change in the market battleground might come too late.
The seek for new opportunities, which usually is based on the thorough and continuous market analysis, just sleeps over.
Your company might have a market research and analysis department, usually sitting in strategy, but the set of analysis produced there is just long term, trend-like where-our-company-needs-to-focus insights
When it comes down to the operations, these insights are usually inappropriate and consequently ignored.
The battles take place in the day-to-day business at a very granular scale: take the next store and ask them how important the constant monitoring of the competence is… Isn’t it the duty of the data exploitation team to support the store manager?
Your most precious assets, just disregarded
The data available in the organization, if properly exploited, enables the definition of a compelling strategy to identify high performers at risk and apply the necessary measures to retain those
The huge amount of money employed for headhunting talents is of no use if your best brains leave your company. Conversely, the proper usage of freely available data in Internet would enable the identification of market experts or your competitors’ elite team, you might want to hit on for the sake of a double win: your +1 is at the same time a -1 for a direct competitor
Having said that regarding high performance, the right data-driven strategy can help organizations uncover low performers, detect unbalanced head counts distribution or adjust the compensation model.
Not taking sounded decisions regarding your most valuable resource is like playing a game you only can win if all others are equally bad and you are lucky… But why taking the risk? A data driven approach instead of a wet finger in the air one is the answer
Your eternal unknown: your customer
The segmentation of the customers turns into a mix of socio-demographic profiling and gut feel (or as a better term, perception). The distance to the customers of the teams with the right skills to deal with the data on one hand and the lack of rigor in the analysis in the business departments or worst the unawareness of the existence of such an essential marketing, sales and retention weapon inherent in the data result into a pseudo shot-gun approach for any kind of communication with both the customers and the prospects –“We know that you are young and we see that you called once our hotline”-. Even with a sophisticated system able to keep track on the interaction of a given customer with each and every channel all along the customer lifetime, if the proper system is not in place, you are not going to able to exploit this information. To bridge this intelligence gap, many organizations decide to define their own segments of customers, creating personas and all the stuff but missing the personalization and the clusters-of-one customers experience tailoring. Your customers are used to you to be deaf and blind, ignoring the signals they are giving you and the mere reason they show you this fictive loyalty, is most probably because your competitors’ aren’t doing any better and your product is with all caveats competitive enough or they are just too lazy to churn… But this is definitively not the place you want to be in and you can only lose sooner rather than later if you continue playing this game.
I hope you don’t find many similitudes between what you have read so far and the organization you work for or you lead. If it is the case, don’t worry… just take it as a wake-up call and react now. My next post is going to tell you exactly how.
Note about the last picture in this post: this picture is not hosted on this site, it’s just a link to existing pictures in the media archive of imdb.com. As stated in the imdb how to link I’m providing the attribution here: